Comments: Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty

Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty

An accurate estimation of the remaining useful life (RUL) and capacity of lithium-ion batteries (LIBs) can guarantee safe and reliable operation and help to make wise replacement decisions. This paper presents an improved approach for predicting the RUL and capacity of LIB using a long short-term me...

Full description

Saved in:

Bibliographic Details
Main Authors:	Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.
Other Authors:	59055914200
Format:	Article
Published:	Institute of Electrical and Electronics Engineers Inc. 2025
Subjects:	Brain Digital storage Forecasting Learning algorithms Lithium-ion batteries Long short-term memory NASA Particle swarm optimization (PSO) Accuracy Battery Capacity prediction Gravitational search algorithm Optimisations Prediction algorithms Predictive models Remaining useful lives Search Algorithms Uncertainty Deep neural networks
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty

Similar Items