Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses

Author:

Altarabichi Mohammed Ghaith,Fan Yuantao,Pashami Sepideh,Mashhadi Peyman Sheikholharam,Nowaczyk Slawomir

Publisher

IEEE

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Improving Concordance Index in Regression-based Survival Analysis: Evolutionary Discovery of Loss Function for Neural Networks;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2024-07-14

2. Electric Vehicle Battery Drain Prediction Using Artificial Intelligence;2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES);2023-12-14

3. Fast Genetic Algorithm for feature selection — A qualitative approximation approach;Proceedings of the Companion Conference on Genetic and Evolutionary Computation;2023-07-15

4. A machine learning-based optimization approach for pre-copy live virtual machine migration;Cluster Computing;2023-05-09

5. A novel state of health estimation approach based on polynomial model for lithium-ion batteries;International Journal of Electrochemical Science;2023-05

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