Lithium-ion battery state of health estimation using automated machine learning (AutoML): performance comparison

Created by W.Langdon from gp-bibliography.bib Revision:1.9129

@Article{Kadem:2026:PeerJ,

• author = "Hasibe Candan Kadem and Onur Kadem",
• title = "Lithium-ion battery state of health estimation using automated machine learning ({AutoML}): performance comparison",
• journal = "PeerJ Computer Science",
• year = "2026",
• pages = "12:e3497",
• month = feb # " 27",
• keywords = "genetic algorithms, genetic programming, TPOT, Automated machine learning, Hyperparameter optimization, Lithium batteries, Li, State of health estimation, Incremental capacity analysis",
• ISSN = "2376-5992",
• URL = "https://peerj.com/articles/cs-3497/",
• URL = "https://peerj.com/articles/cs-3497.pdf",
• DOI = "10.7717/peerj-cs.3497",
• size = "30 pages",
• notes = "'benchmark comparisons show our AutoML pipelines, especially TPOT and FLAML, match or surpass common SoH estimators (GPR, GBRT, Bi-GRU, CNN transfer, CNN-LSTM-DA, EIS-UKF) while minimizing manual search effort and preserving deployability'

  Computer Engineering Department, Bursa Technical University, Bursa, Turkey",

}

Genetic Programming entries for Hasibe Candan Kadem Onur Kadem

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