Stochastic Fractal Search with Chaos

dc.contributor.authorBingöl, Okan
dc.contributor.authorGüvenç, Uğur
dc.contributor.authorDuman, Serhat
dc.contributor.authorPaçacı, Serdar
dc.date.accessioned2020-04-30T23:32:14Z
dc.date.available2020-04-30T23:32:14Z
dc.date.issued2017
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEYen_US
dc.descriptionGUVENC, Ugur/0000-0002-5193-7990; Duman, Serhat/0000-0002-1091-125Xen_US
dc.descriptionWOS: 000426868700071en_US
dc.description.abstractIn this study, the convergence speed and fitness function accuracy have been compared with the original algorithm by developing on the Stochastic Fractal Search (SFS) algorithm. Seven classical mathematical benchmark functions used in testing the optimization algorithms in the literature were used in comparison process. In the original SFS algorithm, the Gaussian walk function is used to find new solution points in diffusion process. The step length in this walk decreases as the iteration progresses and a function depending on generation value is used to provide for a more local search. The improvement in this work is the process of adding chaotic map values to this function. According to simulation results, it is observed that seven chaotic map improves the original algorithm from ten chaotic maps applied to SFS algorithm.en_US
dc.description.sponsorshipIEEE Turkey Sect, Anatolian Scien_US
dc.identifier.isbn978-1-5386-1880-6
dc.identifier.urihttps://hdl.handle.net/20.500.12684/4653
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2017 International Artificial Intelligence And Data Processing Symposium (Idap)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectstochastic fractal searchen_US
dc.subjectoptimization algorithmen_US
dc.subjectchaos theoryen_US
dc.titleStochastic Fractal Search with Chaosen_US
dc.typeConference Objecten_US

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