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

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 fuz...

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Published inReliable and Autonomous Computational Science pp. 367 - 378
Main Authors Park, Keon-Jun, Oh, Sung-Kwun, Kim, Yong-Kab
Format Book Chapter
LanguageEnglish
Published Basel Springer Basel 2010
SeriesAutonomic Systems
Subjects
Fuzzy Neural Network
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ISBN9783034800303
3034800304
DOI10.1007/978-3-0348-0031-0_19

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Summary: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.
ISBN:9783034800303
3034800304
DOI:10.1007/978-3-0348-0031-0_19