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The form of fruit fly optimization algorithm (FOA) is easy to learn and has the characteristics of quick convergence and not readily dropping into local optimum. This paper presents the optimization of RBF neural network by means of FOA and establishment of network model, adopting it with the combination of the evaluation of the mean impact value(MIV) to select variables. The validity of this model is tested by two actual examples, furthermore, it is simpler to learn, more stable and practical. Keywords-FOA; RBF neural network; Parameter optimization; MIV; Variables screen

Variables Screening Method Based on the Algorithm of Combining Fruit Fly Optimization Algorithm and RBF Neural Network