A Hybrid Optimization Method for Fuzzy Classification Systems

This paper presents a hybrid optimization method based on the fusion of the clonal selection algorithm (CSA) and harmony search (HS) technique. The CSA is employed to improve the members of the harmony memory in the HS method. The hybrid optimization algorithm is further used to optimize a fuzzy classification system for the Fisher Iris data classification. Computer simulations results demonstrate the effectiveness of our new approach.

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