Constructing a user-friendly GA-based fuzzy system directly from numerical data

You Wei Teng, Wen June Wang

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


This paper proposes a novel genetic algorithms (GA)-based algorithm to construct a user-friendly fuzzy system for approximating an unknown system with a satisfactory degree of accuracy. In the algorithm, the adequate number of fuzzy rules, the adequate number of membership functions of each input variable, and the parameters of membership functions will be determined automatically; in addition, the dummy input variables will be detected and discarded. Finally, several typical examples are illustrated to show the effectiveness of the algorithm.

Original languageEnglish
Pages (from-to)2060-2070
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number5
StatePublished - Oct 2004


Dive into the research topics of 'Constructing a user-friendly GA-based fuzzy system directly from numerical data'. Together they form a unique fingerprint.

Cite this