"Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification

dc.contributor.authorHaznedar, Bülent
dc.contributor.authorKalınlı, Adem
dc.date.accessioned2019-06-21T12:25:24Z
dc.date.available2019-06-21T12:25:24Z
dc.date.issued2016
dc.departmentHKÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractIn this study, the premise and consequent parameters of ANFIS are optimized using Genetic Algorithm (GA) based on a population algorithm. The proposed approach is applied to the nonlinear dynamic system identification problem. The simulation results of the method are compared with the Backpropagation (BP) algorithm and the results of other methods that are available in the literature. With this study it was observed that the optimisation of ANFIS parameters using GA is more successful than the other methodsen_US
dc.identifier.citationHaznedar B., Kalinli A., "Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification", International Journal of Intelligent Systems and Applications in Engineering, vol.4, pp.44-47, 2016en_US
dc.identifier.doi10.18201/ijisae.266053
dc.identifier.endpage47en_US
dc.identifier.startpage44en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11782/151
dc.identifier.volume4en_US
dc.language.isoen
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectNeuro-Fuzzy, ANFIS, Genetic Algorithm, System Identificationen_US
dc.title"Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification
dc.typeArticle

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