DESTRUCTIVE FUZZY MODELING USING NEURAL GAS NETWORK

In order to construct fuzzy systems automatically, there are many stud ies on combining fuzzy inference with neural networks. In these studie s, fuzzy models using self-organization and vector quantization have b een proposed. It is well known that these models construct fuzzy infer ence rules effectively representing distribution of input data, and no t affected by increment of input dimensions. In this paper, we propose a destructive fuzzy modeling using neural gas network and demonstrate the validity of a proposed method by performing: some numerical examp les.