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Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory

Qingzhen Liu Chao Cai Lei Wu Renwu Yan

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(6)：P.2657-2666,10.

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(6)：P.2657-2666,10.DOI:10.17775/CSEEJPES.2020.03520

Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory

Qingzhen Liu ¹Chao Cai ²Lei Wu ³Renwu Yan⁴

作者信息

1. School of Electric Engineering and Automation,Fuzhou University,Fuzhou 350116,China
2. Quanzhou Electric Power Supply Company,State Grid Fujian Electric Power Company,Quanzhou 362000,China
3. Electrical and Computer Engineering Department,Stevens Institute of Technology,Hoboken,NJ,07030,USA
4. Department of Power System,Fujian University of Technology,Fuzhou 350116,China
折叠

摘要

关键词

Feature space optimization/integrated statistical indicators/oil-paper insulation state/random forest/time domain characteristic/two-level algorithm

分类

信息技术与安全科学

引用本文复制引用

Qingzhen Liu,Chao Cai,Lei Wu,Renwu Yan..Characteristic Optimization Based on Combined Statistical Indicators and Random Forest Theory[J].CSEE Journal of Power and Energy Systems,2024,10(6):P.2657-2666,10.

基金项目

supported by The National Natural Science Foundation of China(61174117) （61174117）

the Foundation of Scientific Research Project of Jinjiang Science and Education Development Center of Fuzhou Univerdity(2019-JJFDKY-33). （2019-JJFDKY-33）

CSEE Journal of Power and Energy Systems

OACSTPCDEI

ISSN：2096-0042

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