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One of the important issues in the design of fuzzy classifier is the formation of fuzzy if-then rules and the membership functions. This paper presents a Niched Pareto Genetic Algorithm (NPGA) approach to obtain the optimal rule-set and the membership function. To develop the fuzzy system the rule set and the membership functions are encoded into the chromosome and evolved simultaneously using NPGA...
One of the important issues in the design of fuzzy classifier is the formation of fuzzy if-then rules and the membership functions. This paper presents a Particle Swarm Optimization (PSO) approach to obtain the optimal rule set and the membership function. To develop the fuzzy system the membership functions and rule set are encoded as particles and evolved simultaneously using PSO. While designing...
A constructing method of fuzzy classifier using kernel k-means clustering algorithm is introduced in this paper. This constructing method are divided into three phases, namely clustering phase, fuzzy rule created phase and parameters modified phase. Firstly, the original sample space is mapped into a high dimensional feature space by selecting appropriate kernel function. In the feature space, training...
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