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Development of Web Based Courseware for Artificial Neural Networks

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dc.creator BİLEN, MEHMET
dc.creator IŞIK, ALİ HAKAN
dc.creator YİĞİT, Tuncay
dc.date 2018-12-31T21:00:00Z
dc.date.accessioned 2020-10-06T09:30:19Z
dc.date.available 2020-10-06T09:30:19Z
dc.identifier 224d9b6e-7950-49f9-8793-9931825d90eb
dc.identifier 10.35378/gujs.473450
dc.identifier https://avesis.sdu.edu.tr/publication/details/224d9b6e-7950-49f9-8793-9931825d90eb/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/55302
dc.description Artificial Neural Networks (ANN) are important data processing algorithms which are used for solving nonlinear problems. Through classical approaches, mathematical infrastructure and complex equations in ANN are difficult to understand. Interactive and multimedia-based courseware has the potential to overcome these difficulties. In this study, a web based educational courseware for ANN was developed to provide an effective and efficient learning environment so that the difficulties can be overcome. This interactive courseware was also enriched with animations and text-based course contents. In addition to this, the effects of ANN parameters' changes were observed directly through graphical results. In this way, users can easily understand the fundamentals and working mechanism of ANN. Without using any commercial libraries, the courseware was developed with ASP.NET , an object-oriented programming language. The courseware supports file formats such as XML, TXT, and CSV so that it can co-operate with other software. "Balance and Scale" data set was used to evaluate the performance of the courseware. 0.9918 accuracy, 1 specificity and 1 sensitivity values were achieved. When this study is compared to previous studies, improvements in terms of visuality, understandability and interactivity can clearly be identified.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Development of Web Based Courseware for Artificial Neural Networks
dc.type info:eu-repo/semantics/article


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