Recurrent Neural Networks and its Applications in Time Series Data

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dc.contributor.authorNazza, Muhannad Akram
dc.contributor.authorAl-Okbi, Nada Khalil
dc.contributor.authorŞahin, Canan Batur
dc.contributor.authorHu, Gang
dc.contributor.authorSumari, Putra
dc.contributor.authorSnasel, Vaclav
dc.contributor.authorAbualigah, Laith
dc.date.accessioned2026-06-19T06:31:58Z
dc.date.available2026-06-19T06:31:58Z
dc.date.issued2025
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description.abstractRecurrent Neural Networks (RNNs) have been extensively embraced for sequencing analysis and sequential data modelling, especially time series data. This paper delves into the principles and applications of the RNNs concentrically time series analysis. The advantages of time series RNNs, including long short-term memory (LSTM) and Gated recurrent units (GRU), are discussed in detail. Different RNN models have been implemented on both synthetic and real-look time series datasets to assess their performance. The results clearly show RNNs outperformed traditional forecasting and pattern recognition methods. Lastly, the issues related to RNN training, namely, vanishing gradients and overfitting, are briefly addressed, and potential improvements for RNNs are outlined. © 2025 Laith Abualigah.
dc.identifier.doi10.1201/9781003516385-8
dc.identifier.endpage64
dc.identifier.isbn978-104045106-9
dc.identifier.isbn978-103283483-2
dc.identifier.scopus2-s2.0-105013378080
dc.identifier.scopusqualityN/A
dc.identifier.startpage57
dc.identifier.urihttps://doi.org/10.1201/9781003516385-8
dc.identifier.urihttps://hdl.handle.net/20.500.12899/4901
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherCRC Press
dc.relation.ispartofA to Z of Deep Learning and AI
dc.relation.publicationcategoryKitap Bölümü - Uluslararası
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260612
dc.subjectPattern Recognition
dc.subjectTime Series Analysis
dc.subjectIts Applications
dc.subjectNeural Network Application
dc.subjectNeural-Networks
dc.subjectRecurrent Neural Network Model
dc.subjectSequencing Analysis
dc.subjectSequential Data
dc.subjectShort Term Memory
dc.subjectTime-Series Analysis
dc.subjectTime-Series Data
dc.subjectTimes Series
dc.subjectLong Short-Term Memory
dc.titleRecurrent Neural Networks and its Applications in Time Series Data
dc.typeBook Chapter

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