Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation

To accurately estimate the battery state of charge (SOC), it is vital to improve the performance of a battery-powered system. This paper employs the recent proposed Evolutionary Mating Algorithm (EMA) for optimizing the weights and biases of Feed-Forward Neural Network (FNN) in estimating the state...

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Մատենագիտական մանրամասներ
Հիմնական հեղինակներ:	Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan Abdul, Abdul Aziz
Ձևաչափ:	Conference or Workshop Item
Լեզու:	English English
Հրապարակվել է:	2023
Խորագրեր:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Առցանց հասանելիություն:	http://umpir.ump.edu.my/id/eprint/38769/1/Metaheuristic%20approach%20for%20optimizing%20neural%20networks%20parameters.pdf http://umpir.ump.edu.my/id/eprint/38769/2/Metaheuristic%20approach%20for%20optimizing%20neural%20networks%20parameters%20in%20battery%20state%20of%20charge%20estimation_ABS.pdf

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http://umpir.ump.edu.my/id/eprint/38769/1/Metaheuristic%20approach%20for%20optimizing%20neural%20networks%20parameters.pdf
http://umpir.ump.edu.my/id/eprint/38769/2/Metaheuristic%20approach%20for%20optimizing%20neural%20networks%20parameters%20in%20battery%20state%20of%20charge%20estimation_ABS.pdf

Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation

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