Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle

This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. The recorded data were obtained from...

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Bibliographic Details
Main Authors: Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari
Format: Article
Language:English
English
Published: Elsevier 2023
Subjects:
QA75 Electronic computers. Computer science
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/39044/
http://umpir.ump.edu.my/id/eprint/39044/1/Using%20the%20evolutionary%20mating%20algorithm%20for%20optimizing%20deep%20learning%20parameters.pdf
http://umpir.ump.edu.my/id/eprint/39044/2/Using%20the%20evolutionary%20mating%20algorithm%20for%20optimizing%20deep%20learning%20parameters%20for%20battery%20state%20of%20charge%20estimation%20of%20electric%20vehicle.pdf

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