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dc.contributor.authorBal, Çağatay
dc.contributor.authorAladağ, Çağdaş Hakan
dc.date.accessioned2022-12-21T12:00:57Z
dc.date.available2022-12-21T12:00:57Z
dc.date.issued2022en_US
dc.identifier.citationBal, Ç. and Ç. H. Aladağ. 2022. "Time Series Modeling with Deep Neural Networks." In Modeling and Advanced Techniques in Modern Economics, 187-209. doi:10.1142/q0346_0009.en_US
dc.identifier.issn978-180061175-7 / 978-180061174-0
dc.identifier.urihttps://hdl.handle.net/20.500.12809/10449
dc.description.abstractDeep neural networks are the latest among powerful artificial intelligence tools. As advanced forms of artificial neural networks, deep nets can be used in various fields and also time series forecasting. Time series forecasting is a major domain which extends to almost all problem-wise applications. Because of this reason, powerful tools as deep networks have become the perfect tools with their modular structure for time series forecasting. In this study, starting from shallow neural networks to advanced deep networks, including convolutional nets and long short-term memories, in-depth analytics are investigated and their results are given with applications and Python codes.en_US
dc.item-language.isoengen_US
dc.publisherWorld Scientific Publishing Co.en_US
dc.relation.isversionof10.1142/q0346_0009en_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNeural networksen_US
dc.titleTime Series Modeling with Deep Neural Networksen_US
dc.item-typebookParten_US
dc.contributor.departmentMÜ, Fen Fakültesi, İstatistik Bölümüen_US
dc.contributor.authorID0000-0002-7823-2712en_US
dc.contributor.institutionauthorBal, Çağatay
dc.identifier.startpage187en_US
dc.identifier.endpage209en_US
dc.relation.journalModeling and Advanced Techniques in Modern Economicsen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US


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