Battery electric vehicle charging load forecasting using LSTM on STL trend, seasonality, and residual decomposition

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Battery electric vehicle charging load forecasting using LSTM on STL trend, seasonality, and residual decomposition

To overcome the challenge of limited high-resolution Battery Electric Vehicle (BEV) charging data, a unique feature engineering technique was implemented. The start-stop electricity charging data from the My Electric Avenue project underwent transformation into a count of concurrent active charging...

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Bibliographic Details
Main Authors:	Syahrizal, Salleh, Roslinazairimah, Zakaria, Siti Roslindar, Yaziz
Format:	Book Chapter
Language:	English English English
Published:	Springer Cham 2024
Subjects:	QA75 Electronic computers. Computer science TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/42504/ http://umpir.ump.edu.my/id/eprint/42504/1/Battery%20electric%20vehicle%20charging%20load%20forecasting%20using%20LSTM%20on%20STL%20trend_ABST.pdf http://umpir.ump.edu.my/id/eprint/42504/2/Battery%20electric%20vehicle%20charging%20load%20forecasting%20using%20LSTM%20on%20STL%20trend.pdf http://umpir.ump.edu.my/id/eprint/42504/3/Recent%20Advances%20on%20Soft%20Computing%20and%20Data%20Mining.pdf

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