A fault prediction method based on modified Genetic Algorithm using BP neural network algorithm

In order to improve fault forecasting model accuracy of back propagation neural network (BPNN), an improved prediction method of optimized BPNN based on Multilevel Genetic Algorithm (MGA) was proposed. We design new chromosome with multilevel structure, improve the encoding mode, fitness function and genetic operator. Which can optimizes the initial values of weights, thresholds and the structure of BPNN synchronously. Enhancing the ability of nonlinear learning and generalization of BPNN. Case study of continuous casting equipment verified that the proposed model with higher prediction accuracy is better than classical BPNN and GA-BPNN prediction method for fault prediction.

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