Abstract: The authors propose a method for designing an efficient fuzzy classifier that consists of a small number of fuzzy rules with only a few antecedent ...

The main design process of a fuzzy classifier is to design an accurate membership function with a proper fuzzy partition approach for efficiently partition the.

The authors propose a method for designing an efficient fuzzy classifier that consists of a small number of fuzzy rules with only a few antecedent fuzzy ...

In this paper, we propose a method for designing an efficient fuzzy classifier that consists of a small number of fuzzy rules with only a few antecedent ...

The authors propose a method for designing an efficient fuzzy classifier that consists of a small number of fuzzy rules with only a few antecedent fuzzy ...

A new method for design of a fuzzy-rule-based classifier using genetic algorithms (GAs) is discussed. The optimal parameters of the fuzzy classifier ...

A new method for design of a fuzzy-rule-based classifier using genetic algorithms (GAs) is discussed.

In this paper, a Fuzzy Genetic Algorithm (FGA) is developed to generate fuzzy classification rules. Several techniques such as multi-value logic coding, ...

Shinn-Ying Ho, Tai-Kang Chen, Shinn-Jang Ho: Designing an Efficient Fuzzy classifier Using an Intelligent Genetic Algorithm. COMPSAC 2000: 293-298.

Oct 22, 2024 · This paper presents a Modified Genetic Algorithm (ModGA) approach to obtain the optimal rule set and the membership function for a fuzzy ...