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dc.contributor.authorAhmad, Iftikhar
dc.contributor.authorMukhtar, Bushra
dc.contributor.authorKutlu, Kadir
dc.contributor.authorAhmad, Farooq
dc.date.accessioned2020-12-19T19:49:05Z
dc.date.available2020-12-19T19:49:05Z
dc.date.issued2017
dc.identifier.citationAhmad, I., Mukhtar, B., Kutlu, K. & Ahmad, F. (2017). A simple neuro-Heuristic computational intelligence algorithm for thin film flow equation arising in physical models. 2017 16Th Ieee International Conference on Machine Learning and Applications (Icmla), 556-561. https://doi.org/10.1109/ICMLA.2017.0-102en_US
dc.identifier.isbn978-1-5386-1417-4
dc.identifier.urihttps://doi.org/10.1109/ICMLA.2017.0-102
dc.identifier.urihttps://hdl.handle.net/11436/2217
dc.description16th IEEE International Conference on Machine Learning and Applications (ICMLA) -- DEC 18-21, 2017 -- Cancun, MEXICOen_US
dc.descriptionWOS: 000425853000085en_US
dc.description.abstractIn this study, computational method are used for finding the approximation in the solution of thin film flow problem using stochastic solver like genetic algorithm (GA) and pattern search (PS). the mathematical model is formulated by defining a fitness function and the process is working in artificial neural networks (ANNs). Proposed numerical results are optimized several times for various values of stoke numbers and material parameters. Different parameters are chosen and several independent number of runs are carried out to find the reliability and accuracy of results. A statistical analysis is presented for the reliability of designed scheme.en_US
dc.description.sponsorshipIEEEen_US
dc.language.isoengen_US
dc.publisherIeeeen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectThin Film Flow equationen_US
dc.subjectNeural networksen_US
dc.subjectlog-sigmoid functionen_US
dc.subjectboundary value problemsen_US
dc.titleA simple neuro-Heuristic computational intelligence algorithm for thin film flow equation arising in physical modelsen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentRTEÜ, Fen - Edebiyat Fakültesi, Matematik Bölümüen_US
dc.contributor.institutionauthorKutlu, Kadir
dc.identifier.doi10.1109/ICMLA.2017.0-102
dc.identifier.startpage556en_US
dc.identifier.endpage561en_US
dc.relation.journal2017 16Th Ieee International Conference on Machine Learning and Applications (Icmla)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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