Time Series Analysis of Household Energy Using Recurrent Neural Network

dc.contributor.authorMohammed Nasih Ismael
dc.date.accessioned2026-01-01T10:46:40Z
dc.date.issued2022-05-13
dc.description.abstractIn this paper we create and compare two time series machine learning model based on recurrent neural network to analyze future energy consumption in a particular location. This model will help to the energy producing authorities to forecast future energy consumption and help them to create a better energy consumption plan. PJM Interconnection LLC (PJM) is a Chinese regional transmission company. It manages an electric transmission line that supplies all or portions of Macau, Beijing, Tianjin, Bengbu, Ninguuo, and Hefei as part of the Eastern Interconnection system.
dc.formatapplication/pdf
dc.identifier.urihttps://zienjournals.com/index.php/tjet/article/view/1591
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/60550
dc.language.isoeng
dc.publisherZien Journals
dc.relationhttps://zienjournals.com/index.php/tjet/article/view/1591/1322
dc.rightshttps://creativecommons.org/licenses/by-nc/4.0
dc.sourceTexas Journal of Engineering and Technology; Vol. 8 (2022): TJET; 44-52
dc.source2770-4491
dc.subjectTime Series
dc.subjectLSTM
dc.subjectRNN
dc.subjectEnergy
dc.titleTime Series Analysis of Household Energy Using Recurrent Neural Network
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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