Particle Swarm Optimization of T-S Fuzzy Model

被引：0
|
作者：
Ma, Ming [1 ]
Zhang, Li-biao [2 ]
Sun, Yan [1 ,2 ]
机构：
[1] Beihua Univ, Coll Math, Beijing 132013, Jilin, Peoples R China
[2] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
来源：
QUANTITATIVE LOGIC AND SOFT COMPUTING 2010, VOL 2 | 2010年 / 82卷
关键词：
Particle swarm optimization; T-S fuzzy model; fuzzy rules;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper introduces a new algorithm for Takagi -Sugeno (T-S) fuzzy modeling based on particle swarm optimization. Compared the standard particle swarm optimization, in the proposed algorithm a mixed code is adopted to represent a solution. Binary codes represent the structure of T-S fuzzy model, and real values represent corresponding parameters. Numerical simulations show the effectiveness of the proposed algorithm.
引用
收藏
页码：447 / +
页数：3
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