SJE főmenü
doc. RNDr. Ferdinánd Filip, PhD.
Név: doc. RNDr. Ferdinánd Filip, PhD.
Megbízott tanszékvezető
Kar: Gazdaságtudományi és Informatikai Kar
Tanszék: Matematika Tanszék
Beosztás: Egyetemi docens
Iroda: TP3A
E-mail:
Telefon: +421 35 32 60 762
A tanulmányi program profiltantárgyáért felelős személy:
Matematika tanári szak (1. és 2. szint, nappali képzés)
Matematika és informatika oktatásának elmélete - Matematika szak (3. szint, nappali képzés)

Egyetemi tanulmányok
Konstantin Filozófus Egyetem, Nyitra, Természettudományi Kar
matematika és fizika szakos tanár
1992 - 1997
Rigorózus eljárás
Konstantin Filozófus Egyetem, Nyitra, Természettudományi Kar
matematika
1999 - 1999
Doktori képzés (PhD.)
Osztravai Egyetem, Osztrava, Természettudományi Kar
Alkalmazott algebra
2001 - 2004
Habilitáció
Osztravai Egyetem, Osztrava, Természettudományi Kar
Alkalmazott matematika
2016

Munkaviszonyok
Nagytárkányi Alapiskola
matematika - fizika szakos tanár
1997 - 1997
Nagykaposi Alapiskola
matematika - fizika szakos tanár
1998 - 2000
Selye János Egyetem
adjunktus
2004 -


Kutatási terület Statisztikus számelmélet





A1 kategória - Tudományos monográfiaszerű könyv jellegű publikációk (AAA, AAB, ABA, ABB, ABC, ABD)
Bejegyzések száma: 0

A2 kategória - Egyéb könyv jellegű publikációk (ACA, ACB, BAA, BAB, BCB, BCI, EAI, CAA, CAB, EAJ, FAI)
Bejegyzések száma: 2
ACB Hazai kiadóknál megjelent főiskolai tankönyvek (1)
FAI Könyv jellegű szerkesztői munkák (1)

B kategória - Nemzetközi adatbázisban jegyzett folyóiratok, szerzői bozonylatok, szabadalmak és felfedezések (ADC, ADD, AEG, AEH, BDC, BDD, CDC, CDD, AGJ)
Bejegyzések száma: 6
ADC Külföldi karentált folyóiratokban megjelent tudományos munkák (6)

C kategória - Egyéb recenzált publikációk (ACC, ACD, ADE, ADF, AEC, AED, AFA, AFB, AFC, AFD, AFE, AFF, AFG, AFH, BBA, BBB, BCK, BDA, BDB, BDE, BDF, BEC, BED, BFA, BFB, BGH, CDE, CDF)
Bejegyzések száma: 15
ADE Külföldi nem karentált folyóiratokban megjelent tudományos munkák (7)
ADF Hazai nem karentált folyóiratokban megjelent tudományos munkák (3)
AEC Külföldi recenzált tudományos tanulmánykötetekben, monográfiákban megjelent tudományos munkák (1)
AFD Hazai tudományos konferencián publikált cikkek (1)
AFH Hazai tudományos konferenciacikkek absztraktjai (3)

N kategória - Egyéb nem recenzált publikációk (ADM, ADN, AEM, AEN, BDM, BDN, CBA, CBB)
Bejegyzések száma: 5
ADM A Web of Science vagy SCOPUS adatbázisban jegyzett külföldi folyóiratokban megjelent tudományos munkák (5)

D kategória - Egyéb - a SZKOM által meghatározott kategóriákon kívüli publikációk
Bejegyzések száma: 0

Bejegyzések száma összesen: 28

Hivatkozások:

[1] Nemzetközi (WoS vagy Scopus) adatbázisban jegyzett külföldi publikációkban megjelent hivatkozások, ill. bírálatok (12)
[2] Nemzetközi (WoS vagy Scopus) adatbázisban jegyzett belföldi publikációkban megjelent hivatkozások, ill. bírálatok (7)
[3] Nemzetközi adatbázisban nem jegyzett, külföldi publikációkban megjelent hivatkozások (1)
[4] Nemzetközi adatbázisban nem jegyzett, belföldi publikációkban megjelent hivatkozások (9)
Összesen 29

Publikációk listája

ACB Hazai kiadóknál megjelent főiskolai tankönyvek
Bejegyzések száma: 1


ACB 001 FILIP, Ferdinánd a Sándor KELEMEN. Függvények és sorozatok. 1. vyd. Komárno: Univerzita J. Selyeho, 2016. 126 s. ISBN 978-80-8122-194-1.


ADC Külföldi karentált folyóiratokban megjelent tudományos munkák
Bejegyzések száma: 6


ADC 001 FILIP, Ferdinánd, Ladislav MIŠÍK a János TÓTH. Dispersion of ratio block sequences and asymptotic density. DOI 10.4064/aa131-2-5 Acta Arithmetica. Vol. 131, no. 2 (2008), p. 183-191. ISSN 0065-1036. CCC, WoS, SCOPUS. IF (2013): 0,421. SNIP (2013): 0,914.

Hivatkozások:
2018  [1] BUKOR, J. - CSIBA, P. Best bounds for dispersion of ratio block sequences for certain subsets of integers. In Annales mathematicae et informaticae. ISSN 1787-5021, 2018, vol. 49, p. 55-60. WoS

2009  [4] BUKOR, J. Remarks on distribution functions of certain block sequences. In Acta Mathematica 12. Nitra : UKF, 2009. ISBN 978-80-8094-614-2, s. 69.



ADC 002 FILIP, Ferdinánd a János TÓTH. Characterization of asymptotic distribution functions of ratio block sequences. DOI 10.1007/s10998-010-2115-2 Periodica Mathematica Hungarica. Vol. 60, no.2 (2010), p. 115-126. ISSN 0031-5303. CCC, WoS, SCOPUS. IF (2013): 0,379. SNIP (2013): 0,987.

Hivatkozások:
2021  [1] SVITEK, SZ. - VONTSZEMŰ, M. On structure of the family of regularly distributed sets with respect to the union. In ANNALES MATHEMATICAE ET INFORMATICAE. ISSN 1787-5021, 2021, vol. 54, p. 109-119. WoS

2019  [4] STRAUCH, O. Distribution of sequences: A theory. Bratislava : House of the Slovak Academy of Sciences, 2019. 591s. ISBN 978-80-224-1734-1.

2016  [3] KRČMARSKÝ, D. - MIŠÍK, L. - VÁCLAVÍKOVÁ, Z. On small sets of distribution functions of ratio block sequences. In Uniform distribution theory. ISSN 1336-913X, 2016, vol. 16, no. 1, p. 165-174.



ADC 003 NOSRATABADI, Saeed, Amirhosein MOSAVI, Puhong DUAN, Pedram GHAMISI, Ferdinánd FILIP, Shahab S. BAND, Uwe REUTER, Joao GAMA a Amir H. GANDOMI. Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods. DOI 10.3390/math8101799 Mathematics. Vol. 8, no. 10 (2020), p. 1799-1823. ISSN 2227-7390 (online). CCC, WoS, SCOPUS.

Q WoS=Q1

ADC 004 FILIP, Ferdinánd, Alexandr JANKOV a Jan ŠUSTEK. On relation between asymptotic and Abel densities. DOI 10.1016/j.jnt.2019.09.007 Journal of Number Theory. Vol. 209 (2020), p. 451-466. ISSN 0022-314X. CCC, WoS, SCOPUS.

Q WoS=Q3 Q Scopus=Q1

ADC 005 BUKOR, József, Ferdinánd FILIP a János TÓTH. Sets with Countably Infinitely Many Prescribed weighted Densities. DOI 10.1216/rmj.2020.50.467 The Rocky Mountain Journal of Mathematics. Vol. 50, no. 2 (2020), p. 467-477. ISSN 0035-7596. CCC, WoS, SCOPUS.

Q WoS=Q4 Q Scopus=Q3

ADC 006 BUKOR, József, Ferdinánd FILIP, János TÓTH a László ZSILINSZKY. On I-< q - and I-<= q-convergence of arithmetic functions. DOI 10.1007/s10998-020-00345-y Periodica Mathematica Hungarica : journal of the János Bolyai Mathematical Society. Vol. 82, no. 2 (2021), p. 125-135. ISSN 0031-5303. CCC, WoS, SCOPUS. IF (2019): 0,693. SNIP (2019): 0,955.

Q WoS=Q3 Q Scopus=Q2


ADE Külföldi nem karentált folyóiratokban megjelent tudományos munkák
Bejegyzések száma: 7


ADE 001 HANČL, Jaroslav a Ferdinánd FILIP. Irrationality measure of sequences. Hiroshima Mathematical Journal. Vol. 35, no. 2 (2005), p. 183-195. ISSN 0018-2079.

ADE 002 TÓTH, János, Ferdinánd FILIP a Peter CSIBA. Distribution of terms of a logarithmic sequence. Annales Mathematicae et Informaticae. Vol. 34 (2007), p. 33-45. ISSN 1787-5021. WoS, SCOPUS.

ADE 003 FILIP, Ferdinánd a Jan ŠUSTEK. An elementary proof that almost all real numbers are normal. Acta Univ. Sapientiae, Mathematica. Roč. 2, č. 1 (2010), s. 99-110. ISSN 1844-6094.

ADE 004 FILIP, Ferdinánd, Kálmán LIPTAI, Ferenc MÁTYÁS a János TÓTH. On the best estimations for dispersions of special ratio block sequences. Annales Mathematicae et Informaticae. Vol. 37, no. 1 (2010), p. 85-93. ISSN 1787-5021. WoS, SCOPUS. SNIP (2013): 0,796.

Hivatkozások:
2018  [1] BUKOR, J. - CSIBA, P. Best bounds for dispersion of ratio block sequences for certain subsets of integers. In Annales mathematicae et informaticae. ISSN 1787-5021, 2018, vol. 49, p. 55-60. WoS



ADE 005 MÁTYÁS, Ferenc, Kálmán LIPTAI, János TÓTH a Ferdinánd FILIP. Polynomials with special coefficients. Annales Mathematicae et Informaticae. Vol. 37, no. 1 (2010), p. 101-106. WoS, SCOPUS. SNIP (2013): 0,796.

Hivatkozások:
2017  [1] SITTHASET, A. - LAOHAKOSOL, V. - MAVECHA, S. Polynomials with generalized Fibonacci number coefficients. In AIP Conference Proceedings. ISSN 0094-243X, 2017, vol. 1905, no. 030034. WoS ; SCOPUS

2013  [1] MANSOUR, T. - SHATTUCK, M. Polynomials whose coefficients are generalized Tribonacci numbers. In Applied Mathematics and Computation. ISSN 0096-3003, 2013, vol. 219, no. 15, p. 8366-8374. WoS ; SCOPUS

2012  [1] MANSOUR, T. - SHATTUCK, M. Polynomials whose coefficients are k-fibonacci numbers. In Annales Mathematicae et Informaticae. ISSN 1787-5021, 2012, vol. 40., p. 57-76. WoS ; SCOPUS



ADE 006 BUKOR, József a Ferdinánd FILIP. Sets with prescribed lower and upper weighted densities. Acta Univ. Sapientiae, Mathematica. Vol. 2, no. 1 (2010), p. 92-98. ISSN 1844-6094.

ADE 007 FILIP, Ferdinánd a Jan ŠUSTEK. Normal Numbers and Cantor Expansions. Uniform Distribution Theory. Vol. 9, no. 2 (2014), p. 93-101. ISSN 1336-913X.


ADF Hazai nem karentált folyóiratokban megjelent tudományos munkák
Bejegyzések száma: 3


ADF 001 TÓTH, János, Ladislav MIŠÍK a Ferdinánd FILIP. On some properties of dispersion of block sequences of positive integers. Mathematica Slovaca. Vol. 54, no. 5 (2004), p. 453-464. ISSN 0139-9918.

Hivatkozások:
2018  [1] BUKOR, J. - CSIBA, P. Best bounds for dispersion of ratio block sequences for certain subsets of integers. In Annales mathematicae et informaticae. ISSN 1787-5021, 2018, vol. 49, p. 55-60. WoS

2015  [2] STRAUCH, O. Distribution functions of ratio sequences. An expository paper. In Tatra Mountains Mathematical Publications. ISSN 1210-3195, 2015, vol. 64, no. 1, p. 133-185. SCOPUS

2009  [4] BUKOR, J. Remarks on distribution functions of certain block sequences. In Acta Mathematica 12. Nitra : UKF, 2009. ISBN 978-80-8094-614-2, s. 69.

2009  [2] BUKOR, J. - CSIBA, P. On estimations of dispersion of ratio block sequences. In Mathematica Slovaca. ISSN 0139-9918, 2009, vol. 59, no. 3, p. 283-290. WoS ; SCOPUS

2008  [2] KIJONKA, V. On calculation of generalized densities. In Mathematica Slovaca. ISSN 0139-9918, 2008, vol. 58., no. 2, p. 155-164. WoS ; SCOPUS

2007  [4] GREKOS, G. - STRAUCH, O. Distribution functions of ratio sequences, II. In Uniform Distribution Theory. ISSN 1336-913X, 2007, vol. 2, no. 1, p. 77.



ADF 002 FILIP, Ferdinánd, Ladislav MIŠÍK a János TÓTH. On distribution functions of certain block sequences. Uniform Distribution Theory. Vol. 2, no. 1 (2007), p. 115-126.

Hivatkozások:
2021  [1] SVITEK, SZ. - VONTSZEMŰ, M. On structure of the family of regularly distributed sets with respect to the union. In ANNALES MATHEMATICAE ET INFORMATICAE. ISSN 1787-5021, 2021, vol. 54, p. 109-119. WoS

2019  [4] STRAUCH, O. Distribution of sequences: A theory. Bratislava : House of the Slovak Academy of Sciences, 2019. 591s. ISBN 978-80-224-1734-1.

2015  [2] STRAUCH, O. Distribution functions of ratio sequences. An expository paper. In Tatra Mountains Mathematical Publications. ISSN 1210-3195, 2015, vol. 64, no. 1, p. 133-185. SCOPUS

2009  [4] BUKOR, J. Remarks on distribution functions of certain block sequences. In Acta Mathematica 12. Nitra : UKF, 2009. ISBN 978-80-8094-614-2, s. 69.



ADF 003 FILIP, Ferdinánd, Ladislav MIŠÍK a János TÓTH. On ratio block sequences with extreme distribution function. DOI 10.2478/s12175-009-0123-6 Mathematica Slovaca. Vol. 59, no. 3. (2009), p. 275-282. ISSN 0139-9918. WoS, SCOPUS. IF (2012): 0,394. SNIP (2013): 0,682.

Hivatkozások:
2021  [1] SVITEK, SZ. - VONTSZEMŰ, M. On structure of the family of regularly distributed sets with respect to the union. In ANNALES MATHEMATICAE ET INFORMATICAE. ISSN 1787-5021, 2021, vol. 54, p. 109-119. WoS

2018  [1] BUKOR, J. - CSIBA, P. Best bounds for dispersion of ratio block sequences for certain subsets of integers. In Annales mathematicae et informaticae. ISSN 1787-5021, 2018, vol. 49, p. 55-60. WoS

2009  [4] BUKOR, J. Remarks on distribution functions of certain block sequences. In Acta Mathematica 12. Nitra : UKF, 2009. ISBN 978-80-8094-614-2, s. 69.




ADM A Web of Science vagy SCOPUS adatbázisban jegyzett külföldi folyóiratokban megjelent tudományos munkák
Bejegyzések száma: 5


ADM 001 BUKOR, József, Ferdinánd FILIP a János TÓTH. A criterion for comparability of weighted densities. DOI 10.12988/ams.2014.43162 Applied Mathematical Sciences. Vol. 8, no. 56 (2014), p. 2793-2799. ISSN 1312-885X. SCOPUS. SNIP (2013): 0,781.

ADM 002 CSIBA, Peter, Ferdinánd FILIP, Attila KOMZSÍK a János TÓTH. On the existence of the generalized gauss composition of means. Annales Mathematicae et Informaticae. Vol. 43 (2014), p. 55-65. ISSN 1787-6117. WoS, SCOPUS. SNIP (2013): 0,796.

Hivatkozások:
2019  [1] KISS, G. The influence of using self-devised multimedia applications on paper results in teaching history of cryptography and steganography. In 13th international technology, education and development cenference. Valencia : Int Assoc technology education & development, 2019. ISBN 978-84-09-08619-1, p.8659-8667. WoS



ADM 003 BUKOR, József, Ferdinánd FILIP a János TÓTH. On properties derived from different types of asymptotic distribution functions of ratio sequences. DOI 10.5486/PMD.2019.8498 Publicationes mathematicae : Debrecen. Vol. 95, no. 1-2 (2019), p. 219-230. ISSN 0033-3883. WoS, SCOPUS. IF (2018): 0,691.

Q WoS=Q3

ADM 004 ARDABILI, Sina Faizollahzadeh, Amir MOSAVI, Pedram GHAMISI, Ferdinánd FILIP, Annamária VÁRKONYINÉ KÓCZY, Uwe REUTER, Timon RABCZUK a Peter M. ATKINSON. COVID-19 Outbreak Prediction with Machine Learning. DOI 10.3390/a13100249 Algorithms. Vol. 13, no. 10 (2020), p. [1-36]. ISSN 1999-4893. WoS, SCOPUS.

Q WoS=Q3 Q Scopus=Q3

ADM 005 TÓTH, János, József BUKOR, Ferdinánd FILIP a Ladislav MIŠÍK. On Ideals Defined by Asymptotic Distribution Functions of Ratio Block Sequences. DOI 10.2298/FIL2112945T Filomat. Vol. 35, no. 12 (2021), p. 3945-3955. ISSN 0354-5180. WoS, SCOPUS. IF (2020): 0,844.

Q WoS=Q3 Q Scopus=Q2


AEC Külföldi recenzált tudományos tanulmánykötetekben, monográfiákban megjelent tudományos munkák
Bejegyzések száma: 1


AEC 001 FILIP, Ferdinánd, Kálmán LIPTAI a János TÓTH. On prime divisors of remarkable sequences. In: Annales Mathematicae et Informaticae. Eger: Institute of Mathematics, 2006, Vol. 33 (2006), p. 45-56. WoS, SCOPUS. SNIP (2016): 0,342.


AFD Hazai tudományos konferencián publikált cikkek
Bejegyzések száma: 1


AFD 001 FILIP, Ferdinánd a János TÓTH. On estimations of dispersions of certain dense block sequences. In: Tatra Mountains Mathematical Publications. Bratislava: Tatra Mountains Mathematical Publications, 2005, Vol. 31 (2005), p. 65-74. WoS. SNIP (2013): 0,239.

Hivatkozások:
2018  [1] BUKOR, J. - CSIBA, P. Best bounds for dispersion of ratio block sequences for certain subsets of integers. In Annales mathematicae et informaticae. ISSN 1787-5021, 2018, vol. 49, p. 55-60. WoS

2015  [2] STRAUCH, O. Distribution functions of ratio sequences. An expository paper. In Tatra Mountains Mathematical Publications. ISSN 1210-3195, 2015, vol. 64, no. 1, p. 133-185. SCOPUS

2009  [4] BUKOR, J. Remarks on distribution functions of certain block sequences. In Acta Mathematica 12. Nitra : UKF, 2009. ISBN 978-80-8094-614-2, s. 69.

2009  [2] BUKOR, J. - CSIBA, P. On estimations of dispersion of ratio block sequences. In Mathematica Slovaca. ISSN 0139-9918, 2009, vol. 59, no. 3, p. 283-290. WoS ; SCOPUS

2008  [2] KIJONKA, V. On calculation of generalized densities. In Mathematica Slovaca. ISSN 0139-9918, 2008, vol. 58., no. 2, p. 155-164. WoS ; SCOPUS

2007  [4] GREKOS, G. - STRAUCH, O. Distribution functions of ratio sequences, II. In Uniform Distribution Theory. ISSN 1336-913X, 2007, vol. 2, no. 1, p. 77.




AFH Hazai tudományos konferenciacikkek absztraktjai
Bejegyzések száma: 3


AFH 001 CSIBA, Peter, Ferdinánd FILIP a János TÓTH. Convergence of sequences defined by means. In: Abstracts of the 8th Joint Conference on Mathematics and Computer Science MaCs´10. Komárno: Univerzita J. Selyeho, 2010, P. [21]. ISBN 978-80-8122-003-6.

AFH 002 FILIP, Ferdinánd, József BUKOR a János TÓTH. On weighted densities. In: Abstracts of the 8th Joint Conference on Mathematics and Computer Science MaCs´10. Komárno: Univerzita J. Selyeho, 2010, P. [22]. ISBN 978-80-8122-003-6.

AFH 003 FILIP, Ferdinánd a Jan ŠUSTEK. Singular functions and normal numbers. Abstracts of the 8th Joint Conference on Mathematics and Computer Science MaCs´10. S. [48].


FAI Könyv jellegű szerkesztői munkák
Bejegyzések száma: 1


FAI 001 BUKOR, József a Ferdinánd FILIP. Abstracts of the 8th Joint Conference on Mathematics and Computer Science: MaCS'10. Komárno: Univerzita J. Selyeho, 2010. 66 s. ISBN 978-80-8122-003-6.





Skupina A1 - Knižné publikácie charakteru vedeckej monografie (AAA, AAB, ABA, ABB, ABC, ABD)

Počet výstupov: 0


Skupina A2 - Ostatné knižné publikácie (ACA, ACB, BAA, BAB, BCB, BCI, CAA, CAB, EAI, EAJ, FAI)

Počet výstupov: 3

ACB Vysokoškolské učebnice vydané v domácich vydavateľstvách (2)

FAI Zostavovateľské práce knižného charakteru (bibliografie, encyklopédie, katalógy, slovníky, zborníky, atlasy...) (1)


Skupina B - Publikácie v karentovaných časopisoch alebo registrované vo WoS a Scopus (ADC, ADD, BDC, BDD, CDC, CDD, ADM, ADN, BDM, BDN)

Počet výstupov: 7

ADC Vedecké práce v zahraničných karentovaných časopisoch (4)

ADM Vedecké práce v zahraničných časopisoch registrovaných v databázach Web of Science alebo SCOPUS (3)


Skupina P - Patenty (AGJ)

Počet výstupov: 0


Skupina D - Ostatné sledované publikácie (ACC, ACD, ADE, ADF, AEC, AED, AEG, AEH, AFA, AFB, AFC, AFD, AFE, AFF, AFG, AFH, AEM, AEN, BBA, BBB, BCK, BDA, BDB, BDE, BDF, BEE, BEF, BFA, BFB, CBA, CBB, CDE, CDF)

Počet výstupov: 0


Skupina O - Iné, nesledované publikácie (AFK, AFL, AGI, CAI, CAJ, CEC, CED, CGC, CGD, CIA, CIB, CJA, CJB, CKA, CKB, DAI, EDI, EDJ, GAI, GHG, GII)

Počet výstupov: 0


Ostatné - mimo kategórií MŠSR

Počet výstupov: 1

V3 Vedecký výstup publikačnej činnosti z časopisu (1)


Počet výstupov spolu: 11


Štatistika ohlasov s kategóriou podľa Vyhlášky č. 456/2012 Z. z: počet ohlasov: 1

Citácie v zahraničných publikáciách registrované v citačných indexoch Web of Science a v databáze SCOPUS: počet ohlasov: 1


Štatistika ohlasov s kategóriou podľa Vyhlášky č. 397/2020 Z. z: počet ohlasov: 141

Citácia v publikácii registrovaná v citačných indexoch: počet ohlasov: 139

Citácia v publikácii vrátane citácie v publikácii registrovanej v iných databázach okrem citačných indexov: počet ohlasov: 2


Štatistika ohlasov: počet ohlasov: 142



Menný zoznam publikácií:


V3 Vedecký výstup publikačnej činnosti z časopisu

Počet výstupov: 1


V3_001 Svitek, Szilárd, Annuš, Norbert, Filip, Ferdinánd. Math Can Be Visual-Teaching and Understanding Arithmetical Functions through Visualization [elektronický dokument]. DOI 10.3390/math10152656 In: Mathematics. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 10, č. 15, art. no. 2656, s. 1-14 [online]. ISSN (online) 2227-7390. [angličtina]


ACB Vysokoškolské učebnice vydané v domácich vydavateľstvách

Počet výstupov: 2


ACB_001 Bukor, József, Csiba, Peter, Filip, Ferdinánd, Jaruska, Ladislav. Függvények nemcsak felvételizőknek. 1 vyd. Komárno: Univerzita J. Selyeho, 2012. ISBN 978-80-8122-035-7. Poznámka: Do vydavateľských údajov bol pridaný príznak 1. vydanie. [maďarčina]


ACB_002 Filip, Ferdinánd, Kelemen, Sándor. Függvények és sorozatok. 1. vyd. Komárno: Univerzita J. Selyeho, 2016. ISBN 978-80-8122-194-1. [maďarčina]


ADC Vedecké práce v zahraničných karentovaných časopisoch

Počet výstupov: 4


ADC_001 Filip, Ferdinánd, Jankov, Alexandr, Šustek, Ján. On relation between asymptotic and Abel densities [elektronický dokument]. DOI 10.1016/j.jnt.2019.09.007 In: Journal of Number Theory. Amsterdam: Elsevier, 2020, č. 209, s. 451-466 [tlačená forma]. ISSN 0022-314X. ISSN (online) 1096-1658. https://www.webofscience.com/wos/ccc/full-record/CCC:000510315400021. [angličtina]


ADC_002 Bukor, József, Filip, Ferdinánd, Tóth, János. Sets with Countably Infinitely Many Prescribed weighted Densities [elektronický dokument]. DOI 10.1216/rmj.2020.50.467 In: The Rocky Mountain Journal of Mathematics. Provo: Rocky Mountain Mathematics Consortium, 2020, Roč. 50, č. 2, s. 467-477 [tlačená forma] [online]. ISSN 0035-7596. ISSN (online) 1945-3795. https://www.webofscience.com/wos/ccc/full-record/CCC:000537771800007. [angličtina]


ADC_003 Nosratabadi, Saeed, Mosavi, Amirhosein, Duan, Puhong, Ghamisi, Pedram, Filip, Ferdinánd, Band, Shahab S., Reuter, Uwe, Gama, Joao, Gandomi, Amir H. Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods [elektronický dokument]. DOI 10.3390/math8101799 In: Mathematics. Bazilej: Multidisciplinary Digital Publishing Institute, 2020, Roč. 8, č. 10, s. 1799-1823 [online]. ISSN (online) 2227-7390. https://www.webofscience.com/wos/ccc/full-record/CCC:000586208600001. [angličtina]


ADC_004 Bukor, József, Filip, Ferdinánd, Tóth, János, Zsilinszky, László. On I-


Ohlasy:

2021 [01] Svitek, Szilárd, Vontszemű, Miklós. On structure of the family of regularly distributed sets with respect to the union [elektronický dokument]. DOI 10.33039/ami.2021.10.001 In: Annales Mathematicae et Informaticae. Eger: EKF Líceum Kiadó, 2021, Roč. 54, 109-119 [tlačená forma]. ISSN 1787-5021. ISSN (online) 1787-6117. [angličtina]


2020 [02] Baláž, Vladimír, Visnyai, Tomáš. I–Convergence of Arithmetical Functions [elektronický dokument]. DOI 10.5772/intechopen.91932 In: Number Theory and Its Applications. London: Intech. IntechOpen, 2020, s. 125-147. ISBN 978-1-83968-051-9. ISBN 978-1-83968-050-2. ISBN (online) 978-1-83968-052-6. [angličtina]


2020 [02] Awel, A. Remarks on the arithmetical function (ap(n)). DOI 10.33773/jum.637104 In: Journal of Universal Mathematics. Mersin: Mersin University, 2020, Roč. 3, č. 2, s. 131-136. ISSN 2618-5660. [angličtina]


2020 [01] Awel, Abdu, Kucukaslan, M. A NOTE ON STATISTICAL LIMIT AND CLUSTER POINTS OF THE ARITHMETICAL FUNCTIONS (a(p) (n)), (gamma(n)) and (tau(n)). DOI 10.22342/jims.26.2.808.224-233 In: JOURNAL OF THE INDONESIAN MATHEMATICAL SOCIETY, 2020, Roč. 26, č. 2, 224-233. ISSN 2086-8952


ADM Vedecké práce v zahraničných časopisoch registrovaných v databázach Web of Science alebo SCOPUS

Počet výstupov: 3


ADM_001 Bukor, József, Filip, Ferdinánd, Tóth, János. On properties derived from different types of asymptotic distribution functions of ratio sequences [elektronický dokument]. DOI 10.5486/PMD.2019.8498 In: Publicationes mathematicae: Debrecen. Debrecín: Debreceni Egyetem. Természettudományi és Technológiai Kar. Matematikai Intézet, 2019, Roč. 95, č. 1-2, s. 219-230 [tlačená forma]. ISSN 0033-3883. ISSN (online) 2064-2849. https://www.scopus.com/record/display.uri?eid=2-s2.0-85074471499&origin=resultslist. https://www.webofscience.com/wos/woscc/full-record/WOS:000480412300014. [angličtina]


Ohlasy:

2021 [01] Svitek, Szilárd, Vontszemű, Miklós. On structure of the family of regularly distributed sets with respect to the union [elektronický dokument]. DOI 10.33039/ami.2021.10.001 In: Annales Mathematicae et Informaticae. Eger: EKF Líceum Kiadó, 2021, Roč. 54, 109-119 [tlačená forma]. ISSN 1787-5021. ISSN (online) 1787-6117. [angličtina]


ADM_002 Ardabili, Sina Faizollahzadeh, Mosavi, Amir, Ghamisi, Pedram, Filip, Ferdinánd, Várkonyiné Kóczy, Annamária, Reuter, Uwe, Rabczuk, Timon, Atkinson, Peter M. COVID-19 Outbreak Prediction with Machine Learning [elektronický dokument]. DOI 10.3390/a13100249 In: Algorithms. Basel: Multidisciplinary Digital Publishing Institute, 2020, Roč. 13, č. 10, art. no. 249, s. [1-36] [online]. ISSN (online) 1999-4893. https://www.webofscience.com/wos/woscc/full-record/WOS:000584017000001. https://www.scopus.com/record/display.uri?eid=2-s2.0-85099545833&origin=resultslist. [angličtina]


Ohlasy:

2022 [01] Şimşek, Hakan, Yangın, Elifnaz. An alternative approach to determination of Covid-19 personal risk index by using fuzzy logic [elektronický dokument]. DOI 10.1007/s12553-021-00624-9 In: Health and Technology. Heidelberg: Springer Publishing Company, 2022. ISSN 21907188. ISSN (online) 21907196


2022 [01] Pillai, Punitha Kumaresa, Durairaj, Devaraj, Samivel, Kanthammal. Deep learning-based forecasting of COVID-19 in India [elektronický dokument]. DOI 10.1520/JTE20200574 In: Journal of Testing and Evaluation. Philadelphia: ASTM International, 2022, Roč. 50, č. 1, [tlačená forma]. ISSN 0090-3973. ISSN (online) 1945-7553


2022 [01] Khurana, Savita, Sharma, Gaurav, Miglani, Neha, Singh, Aman, Alharbi, Abdullah, Alosaimi, Wael, Alyami, Hashem, Goyal, Nitin. An intelligent fine-tuned forecasting technique for covid-19 prediction using neuralprophet model [elektronický dokument]. DOI 10.32604/cmc.2022.021884 In: Computers, Materials & Continua. Henderson: Tech Science Press, 2022, Roč. 71, č. 1, 629-649 [tlačená forma]. ISSN 1546-2218. ISSN (online) 1546-2226


2022 [01] Taherinezhad, Ali, Alinezhad, Alireza. Nations performance evaluation during SARS-CoV-2 outbreak handling via data envelopment analysis and machine learning methods [elektronický dokument]. DOI 10.1080/23302674.2021.2022243 In: International Journal of Systems Science: Operations and Logistics. London: Taylor & Francis Group, 2022. ISSN 23302674. ISSN (online) 23302682


2022 [01] Ziyadidegan, Samira, Razavi, Moein, Pesarakli, Homa, Javid, Amir Hossein, Erraguntla, Madhav. Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning [elektronický dokument]. DOI 10.1007/s00477-021-02148-0 In: Stochastic Environmental Research and Risk Assessment. Berlín: Springer Nature. Springer International Publishing AG, 2022, [tlačená forma]. ISSN 1436-3240. ISSN (online) 1436-3259


2022 [01] Reis, Hatice Catal. COVID-19 diagnosis with deep learning [elektronický dokument]. DOI 10.15446/ing.investig.v42n1.88825 In: Ingenieria e Investigacion. Bogotá: Universidad Nacional de Colombia, 2022, Roč. 42, č. 1. ISSN 01205609. ISSN (online) 22488723


2022 [01] Venkateshkumar, M., Sreedevi, A. G., Lakshmanan, S. A., Yogesh kumar, K. R. Nonlinear Autoregressive Exogenous ANN Algorithm-Based Predicting of COVID-19 Pandemic in Tamil Nadu [elektronický dokument]. DOI 10.1007/978-981-16-2126-0_44 In: Lecture Notes in Networks and Systems. Berlin: Springer Science+Business Media B.V., 2022, 545-560. ISBN 9789811621253. ISSN 23673370. ISSN (online) 23673389


2022 [01] Bhattacharya, Abishek, Ghosh, Goldina, Mandal, Ratna, Ghatak, Sujata, Samanta, Debabrata, Shukla, Vinod Kumar, Mukherjee, Sabyasachi, Dutta, Soumi, Mandal, Ankita. Predictive Analysis of the Recovery Rate from Coronavirus (COVID-19) [elektronický dokument]. DOI 10.1007/978-981-16-4284-5_27 In: Lecture Notes in Networks and Systems. Berlin: Springer Nature. Springer Science+Business Media, 2022, 309-320. ISBN 9789811642838. ISSN 23673370. ISSN (online) 23673389


2022 [01] Mishra, Shashvi, Tyagi, Amit Kumar. The Role of Machine Learning Techniques in Internet of Things-Based Cloud Applications [elektronický dokument]. DOI 10.1007/978-3-030-87059-1_4 In: Internet of Things. Berlin: Springer Science+Business Media B.V., 2022, 105-135. ISSN 21991073. ISSN (online) 21991081


2022 [01] Almalki, Abrar, Gokaraju, Balakrishna, Acquaah, Yaa, Turlapaty, Anish. Regression Analysis for COVID-19 Infections and Deaths Based on Food Access and Health Issues [elektronický dokument]. DOI 10.3390/healthcare10020324 In: Healthcare. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 10, č. 2, [online]. ISSN (online) 2227-9032


2022 [01] Shahmanzari, Masoud, Tanrisever, Fehmi, Eryarsoy, Enes, Şensoy, Ahmet. Managing disease containment measures during a pandemic [elektronický dokument]. DOI 10.1111/poms.13656 In: Production and operations management. Malden: John Wiley & Sons, 2022, [tlačená forma] [online]. ISSN 1059-1478. ISSN (online) 1937-5956


2022 [01] Han, Yifei, Huang, Jinliang, Li, Rendong, Shao, Qihui, Han, Dongfeng, Luo, Xiyue, Qiu, Juan. Impact analysis of environmental and social factors on early-stage COVID-19 transmission in China by machine learning [elektronický dokument]. DOI 10.1016/j.envres.2022.112761 In: Environmental Research: A Multidisciplinary Journal of Environmental Sciences, Ecology, and Public Health. Amsterdam: Elsevier, 2022, Roč. 208, [tlačená forma]. ISSN 0013-9351. ISSN (online) 1096-0953


2022 [01] Tavakoli, Mahdieh, Tavakkoli-Moghaddam, Reza, Mesbahi, Reza, Ghanavati-Nejad, Mohssen, Tajally, Amirreza. Simulation of the COVID-19 patient flow and investigation of the future patient arrival using a time-series prediction model: a real-case study [elektronický dokument]. DOI 10.1007/s11517-022-02525-z In: Medical & Biological engineering & Computing: the journal of the International Federation for Medical and Biological Engineering. Heidelberg: Springer Nature. Springer, 2022, [tlačená forma]. ISSN 0140-0118. ISSN (online) 1741-0444


2022 [01] ArunKumar, K. E., Kalaga, Dinesh V., Mohan Sai Kumar, Ch, Kawaji, Masahiro, Brenza, Timothy M. Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal autoregressive Integrated moving average (SARIMA) for forecasting COVID-19 trends [elektronický dokument]. DOI 10.1016/j.aej.2022.01.011 In: Alexandria Engineering Journal. Amsterdam: Elsevier, 2022, Roč. 61, č. 10, 7585-7603. ISSN 1110-0168. ISSN (online) 2090-2670


2022 [01] Borovkov, Alexey I., Bolsunovskaya, Marina V., Gintciak, Aleksei M. Intelligent Data Analysis for Infection Spread Prediction [elektronický dokument]. DOI 10.3390/su14041995 In: Sustainability. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 14, č. 4, [online]. ISSN (online) 2071-1050


2022 [01] Verma, Hanuman, Mandal, Saurav, Gupta, Akshansh. Temporal deep learning architecture for prediction of COVID-19 cases in India [elektronický dokument]. DOI 10.1016/j.eswa.2022.116611 In: Expert Systems with Applications: An International Journal. Oxford: Elsevier. Pergamon Press, 2022, č. 195, [tlačená forma] [online]. ISSN 0957-4174. ISSN (online) 1873-6793


2022 [01] Samrin, Nishat Ahmed, Suzan, Md Mahmudul Hasan, Hossain, Md Selim, Mollah, Mohammad Sarwar Hossain, Haque, Md Dulal. Analysis of COVID-19 Trends in Bangladesh: A Machine Learning Analysis [elektronický dokument]. DOI 10.1007/978-3-030-90618-4_31 In: AI and IoT for Sustainable Development in Emerging Countries: Challenges and Opportunities. Berlin: Springer Nature. Springer Science+Business Media, 2022, s. 611-625 [tlačená forma] [online]. ISBN 978-3-030-90617-7. ISBN (online) 978-3-030-90618-4


2022 [01] Imad, Muhammad, Hussain, Adnan, Hassan, Muhammad Abul, Butt, Zainab, Sahar, Najm Ul. IoT Based Machine Learning and Deep Learning Platform for COVID-19 Prevention and Control: A Systematic Review [elektronický dokument]. DOI 10.1007/978-3-030-90618-4_26 In: AI and IoT for Sustainable Development in Emerging Countries: Challenges and Opportunities. Berlin: Springer Nature. Springer Science+Business Media, 2022, 523-536 [tlačená forma] [online]. ISBN 978-3-030-90617-7. ISBN (online) 978-3-030-90618-4


2022 [01] Garg, Akshit, Venkataramani, Vijay Vignesh, Karthikeyan, Akshaya, Priyakumar, U. Deva. Modern AI/ML Methods for Healthcare: Opportunities and Challenges [elektronický dokument]. DOI 10.1007/978-3-030-94876-4_1 In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Heidelberg: Springer Verlag, 2022, 3-25. ISBN 9783030948757. ISSN 03029743. ISSN (online) 16113349


2022 [01] Babu, Md Ashraful, Ahmmed, Md Mortuza, Ferdousi, Amena, Mostafizur Rahman, M., Saiduzzaman, Md, Bhatnagar, Vaibhav, Raja, Linesh, Poonia, Ramesh Chandra. The mathematical and machine learning models to forecast the COVID-19 outbreaks in Bangladesh [elektronický dokument]. DOI 10.1080/09720502.2021.2015095 In: Journal of interdisciplinary mathematics. [s.l.]: Taylor & Francis Group, 2022, [tlačená forma] [online]. ISSN 0972-0502. ISSN (online) 2169-012X


2022 [01] Arowolo, Micheal Olaolu, Ogundokun, Roseline Oluwaseun, Misra, Sanjay, Agboola, Blessing Dorothy, Gupta, Brij. Machine learning-based IoT system for COVID-19 epidemics [elektronický dokument]. DOI 10.1007/s00607-022-01057-6 In: Computing. Berlin: Springer Nature. Springer International Publishing AG, 2022, [tlačená forma] [online]. ISSN 0010-485X. ISSN (online) 1436-5057


2022 [01] Mohan, Sumit, Solanki, Anil Kumar, Taluja, Harish Kumar, Anuradha, Singh, Anuj. Predicting the impact of the third wave of COVID-19 in India using hybrid statistical machine learning models: A time series forecasting and sentiment analysis approach [elektronický dokument]. DOI 10.1016/j.compbiomed.2022.105354 In: Computers in Biology and Medicine: an international journal. Amsterdam: Elsevier, 2022, Roč. 144, [tlačená forma] [online]. ISSN 0010-4825. ISSN (online) 1879-0534


2022 [01] Zhou, Binggui, Yang, Guanghua, Shi, Zheng, Ma, Shaodan. Interpretable Temporal Attention Network for COVID-19 forecasting [elektronický dokument]. DOI 10.1016/j.asoc.2022.108691 In: Applied Soft Computing: The Official Journal of the World Federation on Soft Computing (WFSC). Amsterdam: Elsevier, 2022, Roč. 120, [tlačená forma]. ISSN 1568-4946. ISSN (online) 1872-9681


2022 [01] Asif, Zunaira, Chen, Zhi, Stranges, Saverio, Zhao, Xin, Sadiq, Rehan, Olea-Popelka, Francisco, Peng, Changhui, Haghighat, Fariborz, Yu, Tong. Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review [elektronický dokument]. DOI 10.1016/j.scs.2022.103840 In: Sustainable cities and society. [Amsterdam]: Elsevier, 2022, Roč. 81, [tlačená forma] [online]. ISSN 2210-6707. ISSN (online) 2210-6715


2022 [01] Perone, Gaetano. Using the SARIMA model to forecast the fourth global wave of cumulative deaths from COVID-19: Evidence from 12 Hard-Hit Big Countries [elektronický dokument]. DOI 10.3390/econometrics10020018 In: Econometrics, 2022, Roč. 10, č. 2. ISSN (online) 22251146


2022 [01] Comito, Carmela, Pizzuti, Clara. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review [elektronický dokument]. DOI 10.1016/j.artmed.2022.102286 In: Artificial Intelligence in Medicine: an international journal, 2022, Roč. 128, s. [tlačená forma]. ISSN 0933-3657. ISSN (online) 1873-2860


2022 [01] Ebubeogu, Amarachukwu Felix, Ozigbu, Chamberline Ekene, Maswadi, Kholoud, Seixas, Azizi, Ofem, Paulinus, Conserve, Donaldson F. Predicting the number of COVID-19 infections and deaths in USA [elektronický dokument]. DOI 10.1186/s12992-022-00827-3 In: Globalization and health. [London]: Springer Nature. BioMed Central, 2022, Roč. 18, č. 1, [online]. ISSN (online) 1744-8603


2022 [01] Eosina, Puspa, Arymurthy, A. M., Krisnadhi, Adila Alfa. A Non-Uniform continuous cellular automata for analyzing and predicting the spreading patterns of COVID-19 [elektronický dokument]. DOI 10.3390/bdcc6020046 In: Big Data and Cognitive Computing. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 6, č. 2, [tlačená forma]. ISSN (online) 2504-2289


2022 [01] AlAlaween, Wafa' H., Faouri, Noor M., Al-Omar, Sarah H., Hendaileh, Elias M., Almousa, Aya Sama S., AlAlawin, Abdallah H., Abdallah, Omar H., Albashabsheh, Nibal T., Khorsheed, Bilal, Abueed, Omar A. A dynamic nonlinear autoregressive exogenous model for the prediction of COVID-19 cases in Jordan [elektronický dokument]. DOI 10.1080/23311916.2022.2047317 In: Cogent Engineering. Abingdon: Taylor & Francis Group, 2022, Roč. 9, č. 1, s. [online]. ISSN (online) 2331-1916


2022 [01] Munoz-Organero, Mario, Queipo-Alvarez, Paula. Deep spatiotemporal model for COVID-19 forecasting [elektronický dokument]. DOI 10.3390/s22093519 In: Sensors. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 22, č. 9, s. [online] [tlačená forma]. ISSN 1424-3210. ISSN (online) 1424-8220


2022 [01] Saleem, Farrukh, Al-Ghamdi, Abdullah Saad Al-Malaise, Alassafi, Madini O., AlGhamdi, Saad Abdulla. Machine learning, deep learning, and mathematical models to analyze forecasting and epidemiology of COVID-19: A systematic literature review [elektronický dokument]. DOI 10.3390/ijerph19095099 In: International journal of environmental research and public health: open access journal. Basel: Multidisciplinary Digital Publishing Institute, 2022, Roč. 19, č. 9, s. [online] [tlačená forma]. ISSN 1661-7827. ISSN (online) 1660-4601


2022 [01] Galetsi, Panagiota, Katsaliaki, Korina, Kumar, Sameer. The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19 [elektronický dokument]. DOI 10.1016/j.socscimed.2022.114973 In: Social Science & Medicine. Oxford: Elsevier, 2022, Roč. 301, s. [tlačená forma]. ISSN 0277-9536. ISSN (online) 1873-5347


2022 [01] Jaulip, Velentine, Alfred, Rayner. A review on statistical and machine learning approaches to forecasting the occurrence of Covid-19 positive cases [elektronický dokument]. DOI 10.1007/978-981-16-8515-6_12 In: Lecture Notes in Electrical Engineering. [s.l.]: Springer Verlag, 2022, s. 139-155. ISBN 9789811685149. ISSN 18761100. ISSN (online) 18761119


2022 [01] Safi, Samir K., Sanusi, Olajide Idris, Tabash, Mosab I. Forecasting the impact of COVID-19 epidemic on China exports using different time series models [elektronický dokument]. DOI 10.47654/V26Y2022I1P102-127 In: Advances in Decision Sciences. [s.l.]: Asia University, 2022, Roč. 26, č. 1. ISSN 20903359. ISSN (online) 20903367


2022 [01] Jha, Preeti, Tiwari, Aruna, Bharill, Neha, Ratnaparkhe, Milind, Patel, Om Prakash, Harshith, Nilagiri, Solasa, Soundarya Lahari. A novel scalable feature extraction approach for COVID-19 protein sequences and their cluster analysis with kernelized fuzzy algorithm. DOI 10.1109/BigComp54360.2022.00021 In: Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022. [s.l.]: Institute of Electrical and Electronics Engineers, 2022, s. 56-59. ISBN 9781665421973


2022 [01] Vadivel, S., Jayakarthik, R. Predictive analytics on Covid-19 prediction using ResNets. DOI 10.1109/ICCMC53470.2022.9754134 In: Proceedings - 6th International Conference on Computing Methodologies and Communication, ICCMC 2022. [s.l.]: Institute of Electrical and Electronics Engineers, 2022, s. 280-287. ISBN 9781665410281


2022 [01] Morsi, Sami A., Alzahrani, Mohammad Eid. Advanced computing approach for modeling and prediction COVID-19 pandemic [elektronický dokument]. DOI 10.1155/2022/6056574 In: Applied Bionics and Biomechanics. Londýn: Hindawi Limited, 2022, Roč. 2022, [tlačená forma] [online]. ISSN 1176-2322. ISSN (online) 1754-2103


2022 [01] Ding, Yanyu, Li, Jiaxing, Song, Weiliang, Xie, Xiaojin, Wang, Guoqiang. Global COVID-19 epidemic prediction and analysis based on improved dynamic transmission rate model with neural networks [elektronický dokument]. DOI 10.1155/2022/4849928 In: Mathematical Problems in Engineering. London: Hindawi Limited, 2022, Roč. 2022, [tlačená forma] [online]. ISSN 1024-123X. ISSN (online) 1563-5147


2022 [01] Zhao, Yu, Zhang, Rusen, Zhong, Yi, Wang, Jingjing, Weng, Zuquan, Luo, Heng, Chen, Cunrong. Statistical analysis and machine learning prediction of disease outcomes for COVID-19 and pneumonia patients [elektronický dokument]. DOI 10.3389/fcimb.2022.838749 In: Frontiers in Cellular and Infection Microbiology. Lausanne: Frontiers Media, 2022, Roč. 12, [online]. ISSN (online) 2235-2988


2022 [01] Feld, Yannick, Hartmann, Alexander K. Large deviations of a susceptible-infected-recovered model around the epidemic threshold [elektronický dokument]. DOI 10.1103/PhysRevE.105.034313 In: Physical Review E: Statistical, nonlinear, biological, and soft matter physics. College Park: American Institute of Physics . American Physical Society, 2022, Roč. 105, č. 3, [tlačená forma] [online] [CD-ROM]. ISSN 2470-0045. ISSN (online) 2470-0053


2022 [01] Mekahlia, Fatma Zohra, Bouzama, Mohamed Zakaria, Nechar, Sara. Impact of vaccination on COVID-19 spread in real time: Visualization and analysis tool [elektronický dokument]. DOI 10.18280/isi.270213 In: Ingenierie des Systemes d'Information. Edmonton: International Information and Engineering Technology Association, 2022, Roč. 27, č. 2, s. 293-301 [tlačená forma] [online]. ISSN 1633-1311. ISSN (online) 2116-7125


2022 [01] Lavric, Alexandru, Petrariu, Adrian I., Mutescu, Partemie Marian, Coca, Eugen, Popa, Valentin. Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design [elektronický dokument]. DOI 10.3390/s22020503 In: Sensors. Bazilej: Multidisciplinary Digital Publishing Institute, 2022, Roč. 22, č. 2, [online] [tlačená forma]. ISSN 1424-3210. ISSN (online) 1424-8220


2021 [01] Aldhyani, Theyazn H.H., Alkahtani, Hasan. A bidirectional long short-term memory model algorithm for predicting covid-19 in gulf countries [elektronický dokument]. DOI 10.3390/life11111118 In: Life. Bazilej: Multidisciplinary Digital Publishing Institute, 2021, Roč. 11, č. 11, [online]. ISSN (online) 2075-1729


2021 [01] Yadav, Shiwali, Kumar, Rakesh. RT-PCR Result Based Covid-19 Prediction Using Voting Classification Approach. DOI 10.1109/ICOSEC51865.2021.9591816 In: Smart Electronics and Communication (ICOSEC 2021): 2nd International Conference on Smart Electronics and Communication (ICOSEC), 7-9 October 2021, Trichy, India. Piscataway: IEEE, 2021, 1070-1078. ISBN 978-1-6654-3368-6


2021 [01] Giancotti, Monica, Lopreite, Milena, Mauro, Marianna, Puliga, Michelangelo. The role of European health system characteristics in affecting Covid 19 lethality during the early days of the pandemic [elektronický dokument]. DOI 10.1038/s41598-021-03120-2 In: Scientific Reports. Londýn: Springer Nature. Nature Publishing Group, 2021, Roč. 11, č. 1, [online] [tlačená forma]. ISSN (online) 2045-2322


2021 [01] Arslan, Hilal. COVID-19 prediction based on genome similarity of human SARS-CoV-2 and bat SARS-CoV-like coronavirus [elektronický dokument]. DOI 10.1016/j.cie.2021.107666 In: Computers & Industrial Engineering. NewYork: Elsevier. Pergamon Press, 2021, Roč. 161, [tlačená forma] [online]. ISSN 0360-8352. ISSN (online) 1879-0550


2021 [01] Comito, Carmela, Pizzuti, Clara. Predicting COVID-19 with AI techniques: Current research and future directions. DOI 10.1145/3487351.3490958 In: ASONAM '21: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. New York: Association for Computing Machinery, 2021, 518-524 [online]. ISBN 9781450391283


2021 [01] Wan Yaacob, Wan Fairos, Sobri, Norafefah Mohamad, Nasir, Syerina Azlin Md, Nordin, Noor Ilanie, Wan Yaacob, Wan Faizah, Mukhaiyar, Utriweni. Machine learning models for COVID-19 confirmed cases prediction: A meta-analysis approach. DOI 10.1088/1742-6596/2084/1/012013 In: International Conference on Mathematics, Statistics and Computing Technology 2021: 27-28 October 2021, Bangkok, Thailand. Bristol: IOP Publishing, 2021, [online]


2021 [01] Khan, Fatima Nazish, Khanam, Ayesha Ayubi, Ramlal, Ayyagari, Ahmad, Shaban. A Review on Predictive Systems and Data Models for COVID-19 [elektronický dokument]. DOI 10.1007/978-981-15-8534-0_7 In: Studies in Computational Intelligence. Berlin: Springer Science+Business Media B.V., 2021, 123-164. ISSN 1860949X. ISSN (online) 18609503


2021 [01] Luo, Xilin, Duan, Huiming, Xu, Kai. A novel grey model based on traditional Richards model and its application in COVID-19 [elektronický dokument]. DOI 10.1016/j.chaos.2020.110480 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2021, Roč. 142, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2021 [01] Tayarani N., Mohammad H. Applications of artificial intelligence in battling against covid-19: A literature review [elektronický dokument]. DOI 10.1016/j.chaos.2020.110338 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2021, Roč. 142, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2021 [01] Parvez, Sirajum Monir, Rakin, Syed Shahir Ahmed, Asadut Zaman, Md, Ahmed, Istiaq, Alif, Redwanul Alam, Ania-Nin-Ania, Rahman, Rashedur M. A Comparison Between Adaptive Neuro-fuzzy Inference System and Autoregressive Integrated Moving Average in Predicting COVID-19 Confirmed Cases in Bangladesh [elektronický dokument]. DOI 10.1007/978-981-15-8354-4_73 In: Lecture Notes in Networks and Systems. Berlin: Springer Science+Business Media B.V., 2021, 741-754. ISBN 9789811583537. ISSN 23673370. ISSN (online) 23673389


2021 [01] Han, Tao, Gois, Francisco Nauber Bernardo, Oliveira, Ramsés, Prates, Luan Rocha, Porto, Magda Moura de Almeida. Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML [elektronický dokument]. DOI 10.1007/s00500-020-05503-5 In: Soft Computing: a Fusion of Foundations, Methodologies and Applications. Berlin: Springer Science+Business Media B.V., 2021, [tlačená forma] [online]. ISSN 1432-7643. ISSN (online) 1433-7479


2021 [01] Zoha, Naurin, Ghosh, Sourav Kumar, Arif-Ul-Islam, Mohammad, Ghosh, Tusher. A numerical approach to maximize the number of testing of COVID-19 using conditional cluster sampling method [elektronický dokument]. DOI 10.1016/j.imu.2021.100532 In: Informatics in medicine unlocked. Londýn: Elsevier, 2021, Roč. 23, [online]. ISSN (online) 2352-9148


2021 [01] Tiwari, Dimple, Bhati, Bhoopesh Singh. A Deep Analysis and Prediction of COVID-19 in India: Using Ensemble Regression Approach [elektronický dokument]. DOI 10.1007/978-3-030-60188-1_5 In: Studies in Computational Intelligence. Berlin: Springer Science+Business Media B.V., 2021, 97-109. ISSN 1860949X. ISSN (online) 18609503


2021 [01] Al-Aamri, Amira K., Al-Harrasi, Ayaman A., Aal-Abdulsalam, Abdurahman K., Al-Maniri, Abdullah A., Padmadas, Sabu S. Forecasting the SARS COVID-19 pandemic and critical care resources threshold in the Gulf Cooperation Council (GCC) countries: Population analysis of aggregate data [elektronický dokument]. DOI 10.1136/bmjopen-2020-044102 In: BMJ open. Londýn: British Medical Association. BMJ Publishing Group, 2021, Roč. 11, č. 5, [online]. ISSN (online) 2044-6055


2021 [01] Arlis, Syafri, Defit, Sarjon. Machine Learning Algorithms for Predicting the Spread of Covid‒19 in Indonesia [elektronický dokument]. DOI 10.18421/TEM102-61 In: TEM Journal: Technology, Education, Management, Informatics. Novi Pazar: Association for Information Communication Technology Education and Science, 2021, Roč. 10, č. 2, 970-974 [tlačená forma] [online]. ISSN 2217-8309. ISSN (online) 2217-8333


2021 [01] Huang, Wenbo, Ao, Shuang, Han, Dan, Liu, Yuming, Liu, Shuang, Huang, Yaojiang. Data-Driven and Machine-Learning Methods to Project Coronavirus Disease 2019 Pandemic Trend in Eastern Mediterranean. DOI 10.3389/fpubh.2021.602353 In: Frontiers in Public Health. Lausanne: Frontiers Media, 2021, Roč. 9, [online]. ISSN 2296-2565


2021 [01] Iyiola, Olaniyi, Oduro, Bismark, Zabilowicz, Trevor, Iyiola, Bose, Kenes, Daniel. System of time fractional models for COVID-19: Modeling, analysis and solutions [elektronický dokument]. DOI 10.3390/sym13050787 In: Symmetry: Open Access Journal. Bazilej: Multidisciplinary Digital Publishing Institute, 2021, Roč. 13, č. 5, [online]. ISSN (online) 2073-8994


2021 [01] Csutak, Balazs, Polcz, Peeter, Szederkenyi, Gabor. Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion [elektronický dokument]. DOI 10.1109/SACI51354.2021.9465563 In: SACI 2021 - IEEE 15th International Symposium on Applied Computational Intelligence and Informatics, Proceedings. New York: Institute of Electrical and Electronics Engineers, 2021, 91-96. ISBN 978-1-7281-9545-2. ISBN 978-1-7281-9543-8. ISBN (online) 978-1-7281-9544-5


2021 [01] Mbilong, Paul Menounga, Berhich, Asmae, Jebli, Imane, Kassiri, Asmae El, Belouadha, Fatima Zahra. Artificial intelligence-enabled and period-aware forecasting COVID-19 spread [elektronický dokument]. DOI 10.18280/isi.260105 In: Ingenierie des Systemes d'Information. Edmonton: International Information and Engineering Technology Association, 2021, Roč. 26, č. 1, 47-57 [tlačená forma] [online]. ISSN 1633-1311. ISSN (online) 2116-7125


2021 [01] Bansal, Ankita, Jayant, Utkarsh. Covid-19 outbreak modelling using regression techniques. DOI 10.1109/ICIPTM52218.2021.9388347 In: 2021 International Conference on Innovative Practices in Technology and Management (ICIPTM). Piscataway: IEEE, 2021, 113-118 [online]. ISBN 9780738132891


2021 [01] Satu, Md Shahriare, Rahman, Md Khalilur, Rony, Maksud Alam, Shovon, Ahmedur Rahman, Adnan, Md Jane Alam, Howlader, Koushik Chandra, Shamim Kaiser, M. COVID-19: Update, Forecast and Assistant-An Interactive Web Portal to Provide Real-Time Information and Forecast COVID-19 Cases in Bangladesh. DOI 10.1109/ICICT4SD50815.2021.9396786 In: 2021 International Conference on Information and Communication Technology for Sustainable Development, ICICT4SD 2021 - Proceedings. [s.l.]: Institute of Electrical and Electronics Engineers, 2021, 456-460 [online]. ISBN 9781665414609


2021 [01] Khalil, Ruhul Amin, Saeed, Nasir, Masood, Mudassir, Fard, Yasaman Moradi, Alouini, Mohamed Slim, Al-Naffouri, Tareq Y. Deep Learning in the Industrial Internet of Things: Potentials, Challenges, and Emerging Applications [elektronický dokument]. DOI 10.1109/JIOT.2021.3051414 In: IEEE Internet of Things Journal. Piscataway: Institute of Electrical and Electronics Engineers, 2021, Roč. 8, č. 14, 11016-11040 [online]. ISSN (online) 2327-4662


2021 [01] EL Azzaoui, Abir, Singh, Sushil Kumar, Park, Jong Hyuk. SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Healthy City [elektronický dokument]. DOI 10.1016/j.scs.2021.102993 In: Sustainable cities and society. [Amsterdam]: Elsevier, 2021, Roč. 71, [tlačená forma] [online]. ISSN 2210-6707. ISSN (online) 2210-6715


2021 [01] Arora, Gunjan, Joshi, Jayadev, Mandal, Rahul Shubhra, Shrivastava, Nitisha, Virmani, Richa, Sethi, Tavpritesh. Artificial intelligence in surveillance, diagnosis, drug discovery and vaccine development against covid-19 [elektronický dokument]. DOI 10.3390/pathogens10081048 In: Pathogens. Basel: Multidisciplinary Digital Publishing Institute, 2021, Roč. 10, č. 8, [online]. ISSN (online) 2076-0817


2021 [01] Hyman, Meleik, Mark, Calvin, Imteaj, Ahmed, Ghiaie, Hamed, Rezapour, Shabnam, Sadri, Arif M., Amini, M. Hadi. Data analytics to evaluate the impact of infectious disease on economy: Case study of COVID-19 pandemic [elektronický dokument]. DOI 10.1016/j.patter.2021.100315 In: Patterns. Amsterdam: Elsevier. Cell Press, 2021, Roč. 2, č. 8, [online]. ISSN (online) 2666-3899


2021 [01] Marzouk, Mohamed, Elshaboury, Nehal, Abdel-Latif, Amr, Azab, Shimaa. Deep learning model for forecasting COVID-19 outbreak in Egypt [elektronický dokument]. DOI 10.1016/j.psep.2021.07.034 In: Process Safety and Environmental Protection: Official Journal of the European Federation of Chemical Engineering: Part B. London: Institution of Chemical Engineers, 2021, Roč. 153, 363-375 [tlačená forma] [online]. ISSN 0957-5820. ISSN (online) 1744-3598


2021 [01] Quiroz-Juárez, Mario A., Torres-Gómez, Armando, Hoyo-Ulloa, Irma, de León-Montiel, Roberto D.J., U'Ren, Alfred B. Identification of high-risk COVID-19 patients using machine learning [elektronický dokument]. DOI 10.1371/journal.pone.0257234 In: PLoS One. San Francisco: Public Library of Science, 2021, Roč. 16, č. 9, [online]. ISSN (online) 1932-6203. [angličtina]


2021 [01] Çaparoğlu, Ömer Faruk, Ok, Yeşim, Tutam, Mahmut. To restrict or not to restrict? Use of artificial neural network to evaluate the effectiveness of mitigation policies: A case study of Turkey [elektronický dokument]. DOI 10.1016/j.chaos.2021.111246 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2021, Roč. 151, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2021 [01] Nawaz, Saqib Ali, Li, Jingbing, Bhatti, Uzair Aslam, Bazai, Sibghat Ullah, Zafar, Asmat, Bhatti, Mughair Aslam, Mehmood, Anum, ul Ain, Qurat, Shoukat, Muhammad Usman. A hybrid approach to forecast the COVID-19 epidemic trend [elektronický dokument]. DOI 10.1371/journal.pone.0256971 In: PLoS One. San Francisco: Public Library of Science, 2021, Roč. 16, č. 10 October, [online]. ISSN (online) 1932-6203


2021 [01] Nasution, Bahrul Ilmi, Nugraha, Yudhistira, Kanggrawan, Juan Intan, Lukmanto Suherman, Alex. Forecasting of COVID-19 Cases in Jakarta using Poisson Autoregression. DOI 10.1109/ICoICT52021.2021.9527454 In: 2021 9th International Conference on Information and Communication Technology, ICoICT 2021. [s.l.]: Institute of Electrical and Electronics Engineers, 2021, 594-599 [online]. ISBN 9781665404471


2021 [01] Fei, Yiming. Analysis the use of machine learning algorithm-based methods in predicting COVID-19 infection. DOI 10.1145/3500931.3500948 In: ISAIMS 2021: Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences. New York: Association for Computing Machinery, 2021, 88-94 [online]. ISBN 9781450395588


2021 [01] Haghighat, Fatemeh. Predicting the trend of indicators related to Covid-19 using the combined MLP-MC model [elektronický dokument]. DOI 10.1016/j.chaos.2021.111399 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2021, Roč. 152, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2021 [01] Vekaria, Darshan, Kumari, Aparna, Tanwar, Sudeep, Kumar, Neeraj. ξboost: An AI-Based Data Analytics Scheme for COVID-19 Prediction and Economy Boosting [elektronický dokument]. DOI 10.1109/JIOT.2020.3047539 In: IEEE Internet of Things Journal. Piscataway: Institute of Electrical and Electronics Engineers, 2021, Roč. 8, č. 21, 15977-15989 [online]. ISSN (online) 2327-4662


2021 [01] Rahmani, Amir Masoud, Yousefpoor, Efat, Yousefpoor, Mohammad Sadegh, Mehmood, Zahid, Haider, Amir, Hosseinzadeh, Mehdi, Ali Naqvi, Rizwan. Machine learning (Ml) in medicine: Review, applications, and challenges [elektronický dokument]. DOI 10.3390/math9222970 In: Mathematics. Bazilej: Multidisciplinary Digital Publishing Institute, 2021, Roč. 9, č. 22, [online]. ISSN (online) 2227-7390


2021 [01] Saif, Sohail, Das, Priya, Biswas, Suparna. A Hybrid Model based on mBA-ANFIS for COVID-19 Confirmed Cases Prediction and Forecast [elektronický dokument]. DOI 10.1007/s40031-021-00538-0 In: Journal of The Institution of Engineers (India): Series B. New Delhi: Springer India, 2021, Roč. 102, č. 6, 1123-1136. ISSN 22502106. ISSN (online) 22502114


2021 [01] Shetty, Rashmi P., Pai, P. Srinivasa. Forecasting of COVID 19 Cases in Karnataka State using Artificial Neural Network (ANN) [elektronický dokument]. DOI 10.1007/s40031-021-00623-4 In: Journal of The Institution of Engineers (India): Series B. New Delhi: Springer India, 2021, Roč. 102, č. 6, 1201-1211. ISSN 22502106. ISSN (online) 22502114


2021 [01] Feki, Ines, Ammar, Sourour, Kessentini, Yousri, Muhammad, Khan. Federated learning for COVID-19 screening from Chest X-ray images [elektronický dokument]. DOI 10.1016/j.asoc.2021.107330 In: Applied Soft Computing: The Official Journal of the World Federation on Soft Computing (WFSC). Amsterdam: Elsevier, 2021, Roč. 106, [tlačená forma]. ISSN 1568-4946. ISSN (online) 1872-9681


2021 [01] Goo, Taewan, Apio, Catherine, Heo, Gyujin, Lee, Doeun, Lee, Jong Hyeok, Lim, Jisun, Han, Kyulhee, Park, Taesung. Forecasting of the COVID-19 pandemic situation of Korea [elektronický dokument]. DOI 10.5808/gi.21028 In: Genomics & informatics. Seoul: Korea Genome Organization, 2021, Roč. 19, č. 1, [tlačená forma] [online]. ISSN 1598-866X. ISSN (online) 2234-0742


2021 [01] Salam, Mustafa Abdul, Taha, Sanaa, Ramadan, Mohamed. COVID-19 detection using federated machine learning [elektronický dokument]. DOI 10.1371/journal.pone.0252573 In: PLoS One. San Francisco: Public Library of Science, 2021, Roč. 16, č. 6 June, [online]. ISSN (online) 1932-6203


2021 [01] Zivkovic, Miodrag, Bacanin, Nebojsa, Venkatachalam, K., Nayyar, Anand, Djordjevic, Aleksandar, Strumberger, Ivana, Al-Turjman, Fadi. COVID-19 cases prediction by using hybrid machine learning and beetle antennae search approach [elektronický dokument]. DOI 10.1016/j.scs.2020.102669 In: Sustainable cities and society. [Amsterdam]: Elsevier, 2021, Roč. 66, [tlačená forma] [online]. ISSN 2210-6707. ISSN (online) 2210-6715


2021 [01] Naeem, Muhammad, Yu, Jian, Aamir, Muhammad, Khan, Sajjad Ahmad, Adeleye, Olayinka, Khan, Zardad. Comparative analysis of machine learning approaches to analyze and predict the COVID-19 outbreak [elektronický dokument]. DOI 10.7717/PEERJ-CS.746 In: PeerJ. Computer science. San Francisco: Peerj INC, 2021, č. 7, [online]. ISSN (online) 2376-5992


2021 [01] Thange, Uzma, Shukla, Vinod Kumar, Punhani, Ritu, Grobbelaar, Wonda. Analyzing COVID-19 dataset through data mining tool 'Orange' [elektronický dokument]. DOI 10.1109/ICCAKM50778.2021.9357754 In: 2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM - 2021). Piscataway: Institute of Electrical and Electronics Engineers, 2021, 198-203 [online]. ISBN (online) 978-1-7281-9491-2


2021 [01] Nayak, Janmenjoy, Naik, Bighnaraj, Dinesh, Paidi, Vakula, Kanithi, Rao, B. Kameswara, Ding, Weiping, Pelusi, Danilo. Intelligent system for COVID-19 prognosis: a state-of-the-art survey [elektronický dokument]. DOI 10.1007/s10489-020-02102-7 In: Applied Intelligence: the international journal of artificial intelligence, neural networks and complex problems - solving technologies. New York: Springer Nature. Springer International Publishing AG, 2021, Roč. 51, č. 5, 2908-2938 [tlačená forma]. ISSN 0924-669X. ISSN (online) 1573-7497


2021 [01] Satu, Md Shahriare, Howlader, Koushik Chandra, Mahmud, Mufti, Shamim Kaiser, M., Islam, Sheikh Mohammad Shariful, Quinn, Julian M.W., Alyami, Salem A., Moni, Mohammad Ali. Short-term prediction of covid-19 cases using machine learning models [elektronický dokument]. DOI 10.3390/app11094266 In: Applied sciences. Bazilej: Multidisciplinary Digital Publishing Institute, 2021, Roč. 11, č. 9, [online]. ISSN (online) 2076-3417


2021 [01] Silabela, Mxolisi, Bogdandy, Bence, Toth, Zsolt. Automatic Mask Detecion using Convolutional Neural Networks and Variational Autoencoder [elektronický dokument]. DOI 10.1109/SACI51354.2021.9465587 In: SACI 2021 - IEEE 15th International Symposium on Applied Computational Intelligence and Informatics, Proceedings. New York: Institute of Electrical and Electronics Engineers, 2021, 461-466. ISBN 978-1-7281-9545-2. ISBN 978-1-7281-9543-8. ISBN (online) 978-1-7281-9544-5. [angličtina]


2021 [01] Bhattacharya, Sweta, Reddy Maddikunta, Praveen Kumar, Pham, Quoc Viet, Gadekallu, Thippa Reddy, Krishnan S, Siva Rama, Chowdhary, Chiranji Lal, Alazab, Mamoun, Jalil Piran, Md. Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey [elektronický dokument]. DOI 10.1016/j.scs.2020.102589 In: Sustainable cities and society. [Amsterdam]: Elsevier, 2021, Roč. 65, [tlačená forma] [online]. ISSN 2210-6707. ISSN (online) 2210-6715


2021 [01] Sharma, Amit, Baldi, Ashish, Kumar Sharma, Dinesh. How to spot COVID-19 patients: Speech & sound audio analysis for preliminary diagnosis of SARS-COV-2 corona patients [elektronický dokument]. DOI 10.1111/ijcp.14134 In: International Journal of Clinical Practice. Hoboken: John Wiley & Sons, 2021, Roč. 75, č. 6, [tlačená forma]. ISSN 1368-5031. ISSN (online) 1742-1241


2021 [01] Banyal, Siddhant, Dwivedi, Rinky, Gupta, Koyel Datta, Sharma, Deepak Kumar, Al-Turjman, Fadi, Mostarda, Leonardo. Technology landscape for epidemiological prediction and diagnosis of covid-19 [elektronický dokument]. DOI 10.32604/cmc.2021.014387 In: Computers, Materials & Continua. Henderson: Tech Science Press, 2021, Roč. 67, č. 2, 1679-1696 [tlačená forma]. ISSN 1546-2218. ISSN (online) 1546-2226. [angličtina]


2021 [01] Hasan, Ahmed Mudheher, Mahmoud, Aseel Ghazi, Hasan, Zainab Mudheher. Optimized Extreme Learning Machine for Forecasting Confirmed Cases of COVID-19 [elektronický dokument]. DOI 10.22266/ijies2021.0430.44 In: International Journal of Intelligent Engineering and Systems. Fukuoka: Intelligent Network and Systems Society, 2021, Roč. 14, č. 2, 484-494. ISSN 2185310X. ISSN (online) 21853118


2021 [01] Garetto, Michele, Leonardi, Emilio, Torrisi, Giovanni Luca. A time-modulated Hawkes process to model the spread of COVID-19 and the impact of countermeasures. DOI 10.1016/j.arcontrol.2021.02.002 In: Annual reviews in control. Oxford: Elsevier. Pergamon Press, 2021, Roč. 51, 551-563 [tlačená forma]. ISSN 1367-5788. [angličtina]


2021 [01] Podder, Prajoy, Khamparia, Aditya, Rubaiyat Hossain Mondal, M., Rahman, Mohammad Atikur, Bharati, Subrato. Forecasting the Spread of COVID-19 and ICU Requirements [elektronický dokument]. DOI 10.3991/ijoe.v17i05.20009 In: International journal of online and biomedical engineering. Viedeň: International Association of Online Engineering, 2021, Roč. 17, č. 5, 81-99 [online]. ISSN (online) 2626-8493


2021 [01] Khalilpourazari, Soheyl, Hashemi Doulabi, Hossein. Robust modelling and prediction of the COVID-19 pandemic in Canada [elektronický dokument]. DOI 10.1080/00207543.2021.1936261 In: International journal of production research. London: Taylor & Francis Group, 2021, [tlačená forma]. ISSN 0020-7543. ISSN (online) 1366-588X


2021 [01] Shah, Het, Shah, Saiyam, Tanwar, Sudeep, Gupta, Rajesh, Kumar, Neeraj. Fusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends [elektronický dokument]. DOI 10.1007/s00530-021-00818-1 In: Multimedia systems. New York: Springer Publishing Company, 2021. ISSN 0942-4962. ISSN (online) 1432-1882


2021 [01] Raheja, Supriya, Kasturia, Shreya, Cheng, Xiaochun, Kumar, Manoj. Machine learning-based diffusion model for prediction of coronavirus-19 outbreak [elektronický dokument]. DOI 10.1007/s00521-021-06376-x In: Neural Computing and Applications. Berlín: Springer Nature. Springer International Publishing AG, 2021, [tlačená forma] [online]. ISSN 0941-0643. ISSN (online) 1433-3058


2021 [01] Piotrowski, Adam P., Piotrowska, Agnieszka E. Differential evolution and particle swarm optimization against COVID-19 [elektronický dokument]. DOI 10.1007/s10462-021-10052-w In: Artificial Intelligence Review: An International Science and Engineering Journal . Cham: Springer Science+Business Media B.V., 2021, [tlačená forma]. ISSN 0269-2821. ISSN (online) 1573-7462


2021 [01] Brima, Yusuf, Atemkeng, Marcellin, Djiokap, Stive Tankio, Ebiele, Jaures, Tchakounté, Franklin. Transfer learning for the detection and diagnosis of types of pneumonia including pneumonia induced by COVID-19 from chest X-ray images [elektronický dokument]. DOI 10.3390/diagnostics11081480 In: Diagnostics. Bazilej: Multidisciplinary Digital Publishing Institute, 2021, Roč. 11, č. 8, [online]. ISSN (online) 2075-4418


2021 [01] Shakeel, Sheikh Muzaffar, Kumar, Nithya Sathya, Madalli, Pranita Pandurang, Srinivasaiah, Rashmi, Swamy, Devappa Renuka. Covid-19 prediction models: A systematic literature review [elektronický dokument]. DOI 10.24171/J.PHRP.2021.0100 In: Osong Public Health and Research Perspectives. Cheongju: Korea Centers for Disease Control and Prevention, 2021, Roč. 12, č. 4, 215-229. ISSN 22109099. ISSN (online) 22336052


2021 [01] Chahar, Shivam, Roy, Pradeep Kumar. COVID-19: A Comprehensive Review of Learning Models [elektronický dokument]. DOI 10.1007/s11831-021-09641-3 In: Archives of Computational Methods in Engineering. Amsterdam: Springer Nature, 2021, [tlačená forma] [online]. ISSN 1134-3060. ISSN (online) 1886-1784


2021 [01] Khedhiri, Sami. Forecasting COVID-19 infections in the Arabian Gulf region [elektronický dokument]. DOI 10.1007/s40808-021-01332-z In: Modeling earth systems and environment. Heidelberg: Springer Nature. Springer, 2021, [tlačená forma] [online]. ISSN 2363-6203. ISSN (online) 2363-6211


2021 [01] Paiva, Henrique Mohallem, Afonso, Rubens Junqueira Magalhães, Sanches, Davi Gonçalves, Pelogia, Frederico José Ribeiro. Study of the COVID-19 pandemic trending behavior in Israeli cities. DOI 10.1016/j.ifacol.2021.10.244 In: 11th IFAC Symposium on Biological and Medical Systems BMS 2021. Amsterdam: Elsevier, 2021, 133-138 [online]


2021 [01] Gupta, Yogesh, Raghuwanshi, Ghanshyam, Ahmadini, Abdullah Ali H., Sharma, Utkarsh, Mishra, Amit Kumar, Mashwani, Wali Khan, Goktas, Pinar, Alshqaq, Shokrya S., Balogun, Oluwafemi Samson. Impact of Weather Predictions on COVID-19 Infection Rate by Using Deep Learning Models. DOI 10.1155/2021/5520663 In: Complexity. Cairo: Hindawi Publishing Corporation, 2021, Roč. 2021, [online]. ISSN 1076-2787. [angličtina]


2021 [01] Khuhawar, Umrah Zadi, Siddiqui, Isma Farah, Arain, Qasim Ali, Siddiqui, Mokhi Maan, Qureshi, Nawab Muhammad Faseeh. On-Ground Distributed COVID-19 Variant Intelligent Data Analytics for a Regional Territory [elektronický dokument]. DOI 10.1155/2021/1679835 In: Wireless Communications and Mobile Computing. Londýn: Wiley-Hindawi, 2021, Roč. 2021, [online] [tlačená forma]. ISSN 1530-8669. ISSN (online) 1530-8677


2021 [01] Hasri, Hudzaifah, Aris, Siti Armiza Mohd, Ahmad, Robiah. Linear Regression and Holt's Winter Algorithm in Forecasting Daily Coronavirus Disease 2019 Cases in Malaysia: Preliminary Study. DOI 10.1109/NBEC53282.2021.9618763 In: 2021 IEEE National Biomedical Engineering Conference (NBEC). New York: Institute of Electrical and Electronics Engineers, 2021, 157-160 [online]. ISBN 9781665436076


2021 [01] Ortigoza, Gerardo, Zapata, Uriel. Covid-19 Projections: A Simple Machine Learning Approach. DOI 10.1109/ICEV52951.2021.9632647 In: 2021 IEEE International Conference on Engineering Veracruz, ICEV 2021. [s.l.]: Institute of Electrical and Electronics Engineers, 2021, [online]. ISBN 9781665445481


2021 [01] Tintín, Verónica, Florez, Hector. Artificial Intelligence and Data Science in the Detection, Diagnosis, and Control of COVID-19: A Systematic Mapping Study [elektronický dokument]. DOI 10.1007/978-3-030-87013-3_27 In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Berlin: Springer Nature. Springer Science+Business Media, 2021, 354-368. ISBN 9783030870126. ISSN 03029743. ISSN (online) 16113349


2021 [01] Mathur, Sandeep, Datta, Krishnasheesh. Prediction of Covid-19 Cases in India Through Machine Learning Using Python. DOI 10.1109/ICRITO51393.2021.9596116 In: 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021. [s.l.]: Institute of Electrical and Electronics Engineers, 2021, [online]. ISBN 9781665417037


2020 [01] Miralles-Pechuán, Luis, Jiménez, Fernando, Ponce, Hiram, Martínez-Villaseñor, Lourdes. A Methodology Based on Deep Q-Learning/Genetic Algorithms for Optimizing COVID-19 Pandemic Government Actions. DOI 10.1145/3340531.3412179 In: CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. New York: Association for Computing Machinery, 2020, 1135-1144 [online]. ISBN 9781450368599


2020 [01] Wieczorek, Michał, Siłka, Jakub, Woźniak, Marcin. Neural network powered COVID-19 spread forecasting model [elektronický dokument]. DOI 10.1016/j.chaos.2020.110203 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2020, Roč. 140, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2020 [01] Shahid, Farah, Zameer, Aneela, Muneeb, Muhammad. Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM [elektronický dokument]. DOI 10.1016/j.chaos.2020.110212 In: Chaos, Solitons & Fractals: an Interdisciplinary Journal of Nonlinear Science. Amsterdam: Elsevier. Elsevier Science, 2020, Roč. 140, [tlačená forma] [online]. ISSN 0960-0779. ISSN (online) 1873-2887


2020 [01] Golinelli, Davide, Boetto, Erik, Carullo, Gherardo, Nuzzolese, Andrea Giovanni, Landini, Maria Paola, Fantini, Maria Pia. Adoption of digital technologies in health care during the COVID-19 pandemic: Systematic review of early scientific literature. DOI 10.2196/22280 In: Journal of Medical Internet Research. Toronto: JMIR Publications, 2020, Roč. 22, č. 11, [tlačená forma] [online]. ISSN 1438-8871


2020 [01] Jarndal, Anwar, Husain, Saddam, Zaatar, Omar, Gumaei, Talal Al, Hamadeh, Amar. GPR and ANN based Prediction Models for COVID-19 Death Cases. DOI 10.1109/CCCI49893.2020.9256564 In: 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI). New York: Institute of Electrical and Electronics Engineers, 2020, [online]. ISBN 9781728120355


2020 [01] de Lima, Clarisse Lins, da Silva, Cecilia Cordeiro, da Silva, Ana Clara Gomes, Luiz Silva, Eduardo, Marques, Gabriel Souza, de Araújo, Lucas Job Brito, Albuquerque Júnior, Luiz Antônio, de Souza, Samuel Barbosa Jatobá, de Santana, Maíra Araújo, Gomes, Juliana Carneiro, de Freitas Barbosa, Valter Augusto, Musah, Anwar, Kostkova, Patty, dos Santos, Wellington Pinheiro, da Silva Filho, Abel Guilhermino. COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19. DOI 10.3389/fpubh.2020.580815 In: Frontiers in Public Health. Lausanne: Frontiers Media, 2020, Roč. 8, [online]. ISSN 2296-2565


2020 [01] Kushwaha, Shashi, Bahl, Shashi, Bagha, Ashok Kumar, Parmar, Kulwinder Singh, Javaid, Mohd, Haleem, Abid, Singh, Ravi Pratap. Significant applications of machine learning for covid-19 pandemic [elektronický dokument]. DOI 10.1142/S2424862220500268 In: Journal of Industrial Integration and Management. Singapur: World Scientific Publishing, 2020, Roč. 5, č. 4, 453-479. ISSN 24248622. ISSN (online) 24248630


2020 [01] Liao, Zhifang, Lan, Peng, Liao, Zhining, Zhang, Yan, Liu, Shengzong. TW-SIR: time-window based SIR for COVID-19 forecasts [elektronický dokument]. DOI 10.1038/s41598-020-80007-8 In: Scientific Reports. Londýn: Springer Nature. Nature Publishing Group, 2020, Roč. 10, č. 1, [online] [tlačená forma]. ISSN (online) 2045-2322


2020 [01] Gupta, Meenu, Jain, Rachna, Gupta, Akash, Jain, Kunal. Real-time analysis of COVID-19 pandemic on most populated countries worldwide [elektronický dokument]. DOI 10.32604/cmes.2020.012467 In: Computer modeling in engineering & sciences. Henderson: Tech Science Press, 2020, Roč. 125, č. 3, 943-965 [tlačená forma]. ISSN 1526-1492. ISSN (online) 1526-1506


2020 [01] Dey, Lopamudra, Chakraborty, Sanjay, Mukhopadhyay, Anirban. Machine learning techniques for sequence-based prediction of viral–host interactions between SARS-CoV-2 and human proteins [elektronický dokument]. DOI 10.1016/j.bj.2020.08.003 In: Biomedical Journal. Amsterdam: Elsevier B.V., 2020, Roč. 43, č. 5, 438-450 [tlačená forma] [online]. ISSN 2319-4170. ISSN (online) 2320-2890


2020 [01] S, Magesh, V.R, Niveditha, P.S, Rajakumar, S, Radha Ram Mohan, L, Natrayan. Pervasive computing in the context of COVID-19 prediction with AI-based algorithms [elektronický dokument]. DOI 10.1108/IJPCC-07-2020-0082 In: International Journal of Pervasive Computing and Communications. Bingley: Emerald Group Publishing, 2020, Roč. 16, č. 5, 477-487 [tlačená forma] [online]. ISSN 1742-7371. ISSN (online) 1742-738X


2020 [01] Fayyoumi, Ebaa, Idwan, Sahar, Aboshindi, Heba. Machine learning and statistical modelling for prediction of Novel COVID-19 patients case study: Jordan [elektronický dokument]. DOI 10.14569/IJACSA.2020.0110518 In: International Journal of Advanced Computer Science and Applications. Bradford: Science and Information (SAI) Organization, 2020, Roč. 11, č. 5, 122-126 [tlačená forma]. ISSN 2158-107X. ISSN (online) 2156-5570


2020 [01] Mirri, Silvia, Delnevo, Giovanni, Roccetti, Marco. Is a COVID-19 second wave possible in Emilia-Romagna (Italy)? Forecasting a future outbreak with particulate pollution and machine learning [elektronický dokument]. DOI 10.3390/computation8030074 In: Computation. Basel: Multidisciplinary Digital Publishing Institute, 2020, Roč. 8, č. 3, [online]. ISSN (online) 2079-3197


2020 [01] Asteris, Panagiotis G., Douvika, Maria G., Karamani, Chrysoula A., Skentou, Athanasia D., Chlichlia, Katerina, Cavaleri, Liborio, Daras, Tryfon, Armaghani, Danial J., Zaoutis, Theoklis E. A novel heuristic algorithm for the modeling and risk assessment of the covid-19 pandemic phenomenon [elektronický dokument]. DOI 10.32604/CMES.2020.013280 In: Computer modeling in engineering & sciences. Henderson: Tech Science Press, 2020, Roč. 125, č. 2, 815-828 [tlačená forma]. ISSN 1526-1492. ISSN (online) 1526-1506


2020 [01] Xie, Hailun, Zhang, Li, Lim, Chee Peng. Evolving CNN-LSTM Models for Time Series Prediction Using Enhanced Grey Wolf Optimizer [elektronický dokument]. DOI 10.1109/ACCESS.2020.3021527 In: IEEE Access: practical innovations, open solutions. Piscataway: Institute of Electrical and Electronics Engineers, 2020, Roč. 8, 161519-161541 [online]. ISSN (online) 2169-3536


2020 [01] Prashanth, B., Neelima, G., Dule, Chhaya S., Chandra Prakash, T., Tarun Reddy, S. Data Science and Machine Learning Integrated Implementation Patterns for Cavernous Knowledge Discovery from COVID-19 Data. DOI 10.1088/1757-899X/981/2/022004 In: 2020 International Conference on Recent Advancements in Engineering and Management. Bristol: Institute of Physics. IOP Publishing, 2020, [online]


2020 [01] Kumar, Sachin, Veer, Karan. Forecasting of Covid-19 cases using machine learning approach [elektronický dokument]. DOI 10.2174/1573398X17666210129131009 In: Current Respiratory Medicine Reviews. [s.l.]: Bentham Science Publishers, 2020, Roč. 16, č. 4, 240-245 [tlačená forma] [online]. ISSN 1573-398X. ISSN (online) 1875-6387


2020 [01] Shilbayeh, Samar A., Abonamah, Abdullah, Masri, Ahmad A. Partially versus purely data-driven approaches in SARS-CoV-2 prediction [elektronický dokument]. DOI 10.3390/app10165696 In: Applied sciences. Bazilej: Multidisciplinary Digital Publishing Institute, 2020, Roč. 10, č. 16, [online]. ISSN (online) 2076-3417


2020 [01] Smit, Albertus J., Fitchett, Jennifer M., Engelbrecht, Francois A., Scholes, Robert J., Dzhivhuho, Godfrey, Sweijd, Neville A. Winter is coming: A southern hemisphere perspective of the environmental drivers of sars-cov-2 and the potential seasonality of covid-19 [elektronický dokument]. DOI 10.3390/ijerph17165634 In: International journal of environmental research and public health: open access journal. Basel: Multidisciplinary Digital Publishing Institute, 2020, Roč. 17, č. 16, 1-28 [online] [tlačená forma]. ISSN 1661-7827. ISSN (online) 1660-4601


2020 [01] Ghamizi, Salah, Rwemalika, Renaud, Cordy, Maxime, Veiber, Lisa, Bissyandé, Tegawendé F., Papadakis, Mike, Klein, Jacques, Le Traon, Yves. Data-driven Simulation and Optimization for Covid-19 Exit Strategies. DOI 10.1145/3394486.3412863 In: KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. New York: Assoc Computing Machinery, 2020, 3434-3442. ISBN 978-1-4503-7998-4


2020 [01] Prakash, Anupam, Sharma, Piyush, Sinha, Indrajeet Kumar, Singh, Upendra Pratap. Spread Peak Prediction of Covid-19 using ANN and Regression (Workshop Paper). DOI 10.1109/BigMM50055.2020.00062 In: 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). Piscataway: Institute of Electrical and Electronics Engineers, 2020, 356-365 [online]. ISBN 9781728193250


2020 [01] De Moura, Luis Vinicius, Dartora, Caroline Mac Hado, De Oliveira, Christian Mattjie, Barros, Rodrigo Coelho, Da Silva, Ana Maria Marques. A Novel Approach to Differentiate COVID-19 Pneumonia in Chest X-ray. DOI 10.1109/BIBE50027.2020.00078 In: 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). New York: Institute of Electrical and Electronics Engineers, 2020, 446-451 [online]. ISBN 9781728195742


2020 [01] Nikil, Ch H.V.S.S., Dalmia, Hemlata, Pavan Kumar, G. Janaki Rama. Covid-19 outbreak analysis. DOI 10.1109/ICSTCEE49637.2020.9276790 In: 2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE). Piscataway: Institute of Electrical and Electronics Engineers, 2020, 347-350 [online]. ISBN 9781728172132


2020 [01] Sinha, Indrajeet Kumar, Singh, Krishna Pratap, Verma, Shekhar. DP-ANN: A new Differential Private Artificial Neural Network with Application on Health data (Workshop Paper). DOI 10.1109/BigMM50055.2020.00061 In: 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). Piscataway: Institute of Electrical and Electronics Engineers, 2020, 351-355 [online]. ISBN 9781728193250


2020 [01] Gambhir, Ekta, Jain, Ritika, Gupta, Alankrit, Tomer, Uma. Regression Analysis of COVID-19 using Machine Learning Algorithms. DOI 10.1109/ICOSEC49089.2020.9215356 In: 2020 International Conference on Smart Electronics and Communication (ICOSEC). Piscataway: Institute of Electrical and Electronics Engineers, 2020, 65-71 [online]. ISBN 9781728154619


2020 [01] Ionescu, Valeriu Manuel, Enescu, Florentina Magda. Web application for timeline representation of COVID-19 data in Romania. DOI 10.1109/ECAI50035.2020.9223251 In: 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). Piscataway: Institute of Electrical and Electronics Engineers, 2020, [online]. ISBN 9781728168432


2020 [01] Althnian, Alhanoof, Elwafa, Afnan Abou, Aloboud, Nourah, Alrasheed, Hend, Kurdi, Heba. Prediction of COVID-19 individual susceptibility using demographic data: A case study on Saudi Arabia [elektronický dokument]. DOI 10.1016/j.procs.2020.10.051 In: 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. Amsterdam: Elsevier, 2020, [online]. ISSN (online) 1877-0509. [angličtina]


ADM_003 Tóth, János, Bukor, József, Filip, Ferdinánd, Mišík, Ladislav. On Ideals Defined by Asymptotic Distribution Functions of Ratio Block Sequences [elektronický dokument]. DOI 10.2298/FIL2112945T In: Filomat. Niš: Univerzitet u Nišu, 2021, Roč. 35, č. 12, 3945-3955 [tlačená forma] [online]. ISSN 0354-5180. ISSN (online) 2406-0933. [angličtina]


Ohlasy:

2021 [01] Svitek, Szilárd, Vontszemű, Miklós. On structure of the family of regularly distributed sets with respect to the union [elektronický dokument]. DOI 10.33039/ami.2021.10.001 In: Annales Mathematicae et Informaticae. Eger: EKF Líceum Kiadó, 2021, Roč. 54, 109-119 [tlačená forma]. ISSN 1787-5021. ISSN (online) 1787-6117. [angličtina]


FAI Zostavovateľské práce knižného charakteru (bibliografie, encyklopédie, katalógy, slovníky, zborníky, atlasy...)

Počet výstupov: 1


FAI_001 Bukor, József, Filip, Ferdinánd. Abstracts of the 8th Joint Conference on Mathematics and Computer Science: MaCS'10, July 14-17, 2010, Komárno, Slovakia. 1 vyd. Komárno: Univerzita J. Selyeho, 2010. ISBN 978-80-8122-003-6. Poznámka: Do vydavateľských údajov bol pridaný príznak 1. vydanie. [angličtina]





 

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