Wong-Zakai approximation for stochastic models of smoking

MakaleAçık Erişim

Özet

In this study, Wong-Zakai approximation method has been used to obtain approximate solutions for two compartmental models of smoking dynamics. Stratonovich stochastic differential equation systems are obtained for these two stochastic models for the application of Wong-Zakai method. Wong-Zakai method is used together with the predictor-corrector deterministic approximation method where Adams-Bashforth method is used as the predictor pair and Adams-Moulton method is used as the corrector pair. Stochastic Runge-Kutta IV, Euler-Maruyama and stochastic Runge-Kutta strong order 1.0 schemes are also used to investigate the models and the results are compared to the results from Wong-Zakai approximation. The comparison shows that Wong-Zakai method is a reliable tool for the analysis of stochastic models and can be considered as an alternative investigation method for modeling studies. Solution graphs, error graphs and numerical results have been given as evidence to show that Wong-Zakai method can also be a reliable method for analyzing various models. An alternate technique for parallelizing the algorithm has also been given to decrease CPU times for Wong-Zakai method. This technique is suggested to overcome the extra calculation load that comes with Wong-Zakai method.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/14449Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.14744/sigma.2023.00114Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorŞengül, Süleyman
dc.contributor.authorBeki̇Ryazici, Zafer
dc.contributor.authorMerdan, Mehmet
dc.date.accessioned2026-10-22T10:22:43.001560085Z
dc.date.available2026-10-22T10:22:43.001560085Z
dc.date.issued2023
dc.description.abstractIn this study, Wong-Zakai approximation method has been used to obtain approximate solutions for two compartmental models of smoking dynamics. Stratonovich stochastic differential equation systems are obtained for these two stochastic models for the application of Wong-Zakai method. Wong-Zakai method is used together with the predictor-corrector deterministic approximation method where Adams-Bashforth method is used as the predictor pair and Adams-Moulton method is used as the corrector pair. Stochastic Runge-Kutta IV, Euler-Maruyama and stochastic Runge-Kutta strong order 1.0 schemes are also used to investigate the models and the results are compared to the results from Wong-Zakai approximation. The comparison shows that Wong-Zakai method is a reliable tool for the analysis of stochastic models and can be considered as an alternative investigation method for modeling studies. Solution graphs, error graphs and numerical results have been given as evidence to show that Wong-Zakai method can also be a reliable method for analyzing various models. An alternate technique for parallelizing the algorithm has also been given to decrease CPU times for Wong-Zakai method. This technique is suggested to overcome the extra calculation load that comes with Wong-Zakai method.
dc.identifier.doi10.14744/sigma.2023.00114
dc.identifier.eissn1304-7191
dc.identifier.endpage968
dc.identifier.issn1304-7191
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85176562230
dc.identifier.startpage958
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/14449
dc.identifier.volume41
dc.identifier.wosWOS:001092577800001
dc.language.isoen
dc.publisherYildiz Technical University
dc.relation.ispartofSigma Journal of Engineering and Natural Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEuler-Maruyama Method
dc.subjectStochastic Differential Equation
dc.subjectStochastic Runge-Kutta Method
dc.subjectWong-Zakai Approximation
dc.subject.classificationEngineering, Multidisciplinary
dc.subject.classificationEngineering
dc.subject.otherNUMERICAL-SOLUTION
dc.subject.otherDYNAMICS
dc.subject.otherEQUATIONS
dc.subject.otherCOVID-19
dc.titleWong-Zakai approximation for stochastic models of smoking
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex0
rdl.citation.scopus2
rdl.citation.wos2
rdl.oa.statusgold
rdl.oa.urlhttp://dx.doi.org/10.14744/sigma.2023.00114
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexEmerging Sources Citation Index (ESCI)