A web-based intelligent educational laboratory system for forecasting chaotic time series

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dc.contributor.authorKose U.
dc.contributor.authorArslan A.
dc.date.accessioned2020-03-26T18:58:58Z
dc.date.available2020-03-26T18:58:58Z
dc.date.issued2014
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn the context of Chaos Theory and its applications, forecasting time series of a chaotic system is an attractive work area for the current literature. Many different approaches and the related scientific studies have been introduced and done by researchers since the inception of this working area. Newer studies are also performed in order to provide more effective and efficient approaches and improve the related literature in this way. On the other hand, it is another important research point to ensure effective educational approaches for teaching Chaos Theory and chaotic systems within the associated courses. In this sense, this chapter introduces a Web-based, intelligent, educational laboratory system for forecasting chaotic time series. Briefly, the system aims to enable students to experience their own learning process over the Web by using a simple interface. The laboratory system employs an Artificial Intelligence-based approach including a Single Multiplicative Neuron System trained by Intelligent Water Drops Algorithm in order to forecast time series of chaotic systems. It is possible to adjust parameters of the related Artificial Intelligence techniques, so it may possible for students to have some knowledge about Artificial Intelligence and intelligent systems. © 2015 by IGI Global. All rights reserved.en_US
dc.identifier.doi10.4018/978-1-4666-6276-6.ch007en_US
dc.identifier.endpage135en_US
dc.identifier.isbn9781466662780; 9781466662773
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage110en_US
dc.identifier.urihttps://dx.doi.org/10.4018/978-1-4666-6276-6.ch007
dc.identifier.urihttps://hdl.handle.net/20.500.12395/31362
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIGI Globalen_US
dc.relation.ispartofArtificial Intelligence Applications in Distance Educationen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA web-based intelligent educational laboratory system for forecasting chaotic time seriesen_US
dc.typeBook Chapteren_US

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