Using active learning in motor control and matlab simulation

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dc.contributor.author Yılmaz, Nurcan Ercan
dc.contributor.author Battal, Onur
dc.date.accessioned 2021-04-09T08:00:48Z
dc.date.available 2021-04-09T08:00:48Z
dc.date.issued 2015-08
dc.identifier.citation Yilmaz, Ercan Nurcan, and Onur Battal. "Using active learning in motor control and matlab simulation." Journal of Automation and Control Engineering 3.4 (2015). tr_TR
dc.identifier.issn 2315-4462
dc.identifier.uri http://hdl.handle.net/20.500.11787/1262
dc.description.abstract —People's desire to produce systems capable of learning and decision making, has led to the concept of artificial intelligence. One of the many ways that is used in the design of intelligent systems is artificial neural networks. Artificial neural networks are computational networks which attempt to simulate the networks of nerve cell (neurons) like central nervous system of the living. Designing any intelligent control system is possible by modeling. In this paper, solid modeling, and the four axes of motion of a robot arm, the starting point positioning with servo motors of the simulation of neural networks with active learning strategies which types of learning are presented. tr_TR
dc.language.iso eng tr_TR
dc.publisher Journal of Automation and Control Engineering tr_TR
dc.relation.isversionof 10.12720/joace.3.4.299-303 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject active learning, artificial neural networks, servo motor tr_TR
dc.title Using active learning in motor control and matlab simulation tr_TR
dc.type article tr_TR
dc.contributor.department Nevşehir Hacı Bektaş Veli Üniversitesi, Hacıbektaş Meslek Yüksekokulu, Elektronik ve Otomasyon Bölümü tr_TR
dc.contributor.authorID 21058 tr_TR
dc.identifier.volume 3 tr_TR
dc.identifier.issue 4 tr_TR
dc.identifier.startpage 299 tr_TR
dc.identifier.endpage 303 tr_TR


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