Design of Interval Type-2 Fuzzy Set-based Fuzzy Neural Networks Using Successive Tuning Method

被引：0
|
作者：
Park, Keon-Jun [1 ]
Oh, Sung-Kwun [1 ]
Kim, Yong-Kab [2 ]
机构：
[1] Univ Suwon, Dept Elect Engn, San 2-2 Wau Ri, Hwaseong Si 445743, Gyeonggi Do, South Korea
[2] Wonkwang Univ, Dept Elect & Elect Engn, Choksan 570749, South Korea
来源：
RELIABLE AND AUTONOMOUS COMPUTATIONAL SCIENCE | 2011年
基金：
新加坡国家研究基金会;
关键词：
LOGIC SYSTEMS;
D O I：
10.1007/978-3-0348-0031-0_19
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we introduce the design methodology of interval type-2 fuzzy set-based fuzzy neural networks (IT2FSFNN). IT2FSFNN is the network of combination between the fuzzy neural network (FNN) and interval type-2 fuzzy set with uncertainty. The premise part of the network is composed of the fuzzy division of respective input space and the consequence part of the network is represented by polynomial functions with interval set. To determine the structure and estimate the values of the parameters of IT2FSFNN we consider the successive tuning method with generation-based evolution by means of genetic algorithms. The proposed network is evaluated with the use of numerical experimentation.
引用
收藏
页码：367 / +
页数：2
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