A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

被引:85
作者
Ramos, Caio C. O. [1 ]
Souza, Andre N. [2 ]
Chiachia, Giovani [3 ]
Falcao, Alexandre X. [3 ]
Papa, Joao P. [4 ,5 ]
机构
[1] Univ Sao Paulo, Dept Elect Engn, Polytech Sch, Sao Paulo, Brazil
[2] UNESP Univ Estadual Paulista, Dept Elect Engn, Bauru, Brazil
[3] Univ Estadual Campinas, Inst Comp, Campinas, SP, Brazil
[4] UNESP Univ Estadual Paulista, Dept Comp, Bauru, Brazil
[5] UNESP Univ Estadual Paulista, Dept Comp Sci, Bauru, Brazil
基金
巴西圣保罗研究基金会;
关键词
D O I
10.1016/j.compeleceng.2011.09.013
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Finding an optimal subset of features that maximizes classification accuracy is still an open problem. In this paper, we exploit the speed of the Harmony Search algorithm and the Optimum-Path Forest classifier in order to propose a new fast and accurate approach for feature selection. Comparisons to some other pattern recognition and feature selection techniques showed that the proposed hybrid algorithm for feature selection outperformed them. The experiments were carried out in the context of identifying non-technical losses in power distribution systems. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:886 / 894
页数:9
相关论文
共 22 条
[1]  
[Anonymous], 2011, ACM T INTEL SYST TEC
[2]  
[Anonymous], 2003, IMPLEMENTATION FAST
[3]  
[Anonymous], LECT NOTES COMPUTER
[4]  
Diao Ren, 2010, P 19 INT C FUZZ SYST, P3161
[5]   The image foresting transform: Theory, algorithms, and applications [J].
Falcao, AX ;
Stolfi, J ;
Lotufo, RDA .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (01) :19-29
[6]  
Fan RE, 2008, J MACH LEARN RES, V9, P1871
[7]  
Firpi H. A., 2004, Proceedings. 33rd Applied Imagery Pattern Recognition Workshop, P112
[8]   Novel derivative of harmony search algorithm for discrete design variables [J].
Geem, Zong Woo .
APPLIED MATHEMATICS AND COMPUTATION, 2008, 199 (01) :223-230
[9]  
Kennedy J, 1997, IEEE SYS MAN CYBERN, P4104, DOI 10.1109/ICSMC.1997.637339
[10]  
Kennedy J. F., 2001, Swarm intelligence