Designing Optimal Fuzzy Classifier Using Particle Swarm Optimization
Subject Areas : electrical and computer engineering
Seyed-Hamid
Zahiri
1
(University of Birjand)
Keywords: Particle swarm optimization fuzzy classifier membership function,
Abstract :
An important issue in designing a fuzzy classifier is setting its structural and mathematical fuzzy parameters (e.g., number of rules, antecedents, consequents, types and locations of membership functions). In fact, the variations of these parameters establish a wide range high dimensional search space, which makes heuristic methods some suitable candidates to solve this problem (designing optimal fuzzy parameters). In this paper, a method is described for this purpose. In presented technique, all fuzzy parameters of a fuzzy classifier, are interpreted in structure of particles and PSO algorithm is employed to find the optimal one. Extensive experimental results on well-known benchmarks and practical pattern recognition problem (automatic target recognition) demonstrate the effectiveness of the proposed method.
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