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A REVIEW OF CHAOS THEORY PRACTICED IN NEURAL NETWORK

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dc.contributor.authorPekel, Engin
dc.contributor.authorKara, Selin Soner
dc.date.accessioned2026-06-27T14:06:22Z
dc.date.issued2016
dc.description.abstractIn this paper, a review of chaos theory, which has been practiced in neural network since 2000, has been presented. A short introduction for chaos theory in the field of artificial neural network has been presented to clarify connection between chaos and different neural network architectures. Phase space construction that covers the time delay, embedding dimension, Lyapunov exponent and fractal dimension has been described in the scope of the introduction of chaos theory. Moreover, neural networks, which have been mostly practiced with chaos theory, have been stated. This study aims to clarify the integrated application between chaos theory and different neural network architectures. This paper would guide future research directions in distinct fields and present the methods to be exerted in neural network.en
dc.identifier.endpage1110
dc.identifier.isbn978-981-3146-96-9
dc.identifier.startpage1105
dc.identifier.urihttps://hdl.handle.net/20.500.14981/57067
dc.identifier.volume10
dc.identifier.wos000417158200170
dc.language.isoeng
dc.publisherWORLD SCIENTIFIC PUBL CO PTE LTD
dc.relation.conference12th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS)
dc.relation.ispartofUNCERTAINTY MODELLING IN KNOWLEDGE ENGINEERING AND DECISION MAKING
dc.subjectSUPPORT VECTOR MACHINE
dc.subjectTIME-SERIES MODELS
dc.subjectPREDICTION
dc.subjectALGORITHM
dc.subjectComputer Science
dc.titleA REVIEW OF CHAOS THEORY PRACTICED IN NEURAL NETWORK
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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