Key parameters of LightGBM.

Key parameters of LightGBM.

<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil...

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Bibliographic Details
Main Author: Jizhong Wang (7441697) (author)
Other Authors: Jianfei Chi (20752518) (author), Yeqiang Ding (20752521) (author), Haiyan Yao (18501084) (author), Qiang Guo (218747) (author)
Published: 2025
Subjects:
Molecular Biology
Biotechnology
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
principal component analysis
obtain joint features
fault diagnosis performance
experimental results show
eliminate information redundancy
construct fused features
uncoded ratio method
fault diagnosis method
oil immersed transformers
ssa algorithm optimization
lightgbm model proposed
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ssa lightgbm
lightgbm oil
feature matrix
feature fusion
effectively improve
dissolved gases
diagnostic accuracy
classification ability
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