FRBPSO: A Fuzzy Rule Based Binary PSO for Feature Selection

被引：0
|
作者：
Shikha Agarwal
R. Rajesh
Prabhat Ranjan
机构：
[1] Central University of South Bihar,Department of Computer Science
[2] Central University of Kerala,Department of Computer Science
来源：
Proceedings of the National Academy of Sciences, India Section A: Physical Sciences | 2017年 / 87卷
关键词：
Particle swarm optimization; Fuzzy logic; Fuzzy rule based PSO; Classification; Feature selection;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Particle swarm optimization and fuzzy logic have shown their fruits for many years across the fields of science. Fuzzy logic acts as an intelligent layer to any conventional system. Recently fuzzy logic has been used to improve the performance of particle swarm optimization (PSO). This paper presents a novel fuzzy rule based binary PSO (FRBPSO) for feature selection to get better classification and a survey on the PSO fuzzy logic hybrid methods. The results on benchmarking high dimensional microarray datasets show the merits of the proposed FRBPSO method.
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页码：221 / 233
页数：12
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