Optimized LightGBM Power Fingerprint Identification Based on Entropy Features.

Lin, Lin; Zhang, Jie; Zhang, Na; Shi, Jiancheng; Chen, Cheng

Lin, Lin; Zhang, Jie; Zhang, Na; Shi, Jiancheng; Chen, Cheng.

Afiliación

Lin L; College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China.
Zhang J; College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China.
Zhang N; State Grid Liaoning Economic Research Institute, Shenyang 110015, China.
Shi J; College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China.
Chen C; College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China.

Entropy (Basel) ; 24(11)2022 Oct 29.

Article en En | MEDLINE | ID: mdl-36359649

Palabras clave

Boruta algorithm; LightGBM; Optuna algorithm; entropy feature; power fingerprint

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Entropy (Basel) Año: 2022 Tipo del documento: Article País de afiliación: China

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