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A new optimal algorithm for fuzzy model is presented on chaos optimization. In the model, fuzzy inference rules are transformed to be fuzzy radial basis function(RBF) network model, which combines the chaos algorithm with the typical clustering algorithms such as fuzzy C means(FCM) clustering algorithm to study parameters of fuzzy neural network. At first, FCM clustering algorithm and partition effect entropy are used to obtain model structure. And then the initial parameters of clustering centers are gotten by synthetical chaos series and the most optimal clustering center is obtained by FCM. Last fuzzy neural network model is achieved. A example is presented to illustrate the performance and applicability of the proposed model and simulation results show excellent performance.