Feature Selection of Power Quality Disturbance Signals with an Entropy-Importance-Based Random Forest

Power quality signal feature selection is an effective method to improve the accuracy and efficiency of power quality (PQ) disturbance classification. In this paper, an entropy-importance (EnI)-based random forest (RF) model for PQ feature selection and disturbance classification is proposed. Firstl...

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Main Authors: Nantian Huang, Guobo Lu, Guowei Cai, Dianguo Xu, Jiafeng Xu, Fuqing Li, Liying Zhang
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2016-01-01
Colecção:Entropy
Assuntos:
power quality
power quality disturbances
random forest
S-transform
feature selection
entropy-importance
sequential forward search
Acesso em linha:http://www.mdpi.com/1099-4300/18/2/44
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