Fuzzy Particle Swarm Optimization Algorithm

被引：24
|
作者：
Tian, Dong-ping [1 ]
Li, Nai-qian [1 ]
机构：
[1] Baoji Univ Arts & Sci, Inst Comp Software, Baoji 721007, Shaanxi, Peoples R China
来源：
FIRST IITA INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2009年
关键词：
Fuzzy logic controller(FLC); Inertia weight Learning coefficient; Canonical particle swarm optimization(CPSO);
D O I：
10.1109/JCAI.2009.50
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a novel fuzz), particle swarm optimization(NFPSO), in which inertia weight as well as the learning coefficient can be adaptively adjusted according to the control information translated from the fuzzy logic controller (FLC) during the search process, is presented by introducing a two-input and two-output FLC into the canonical particle swarm optimization (CPSO). The effectiveness of NFPSO proposed in this paper is demonstrated by applying it to three benchmark functions obtained from the literature. The simulation results show that NFPSO outperforms CPSO and other fuzzy PSO versions.
引用
收藏
页码：263 / 267
页数：5
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