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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Elsevier
2023
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| Subjects: | |
| 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 |
Internet
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