Application of BP Neural Network Based on Genetic Algorithm Optimization

Abstract

In order to improve the accuracy of the BP neural network prediction model to predict the transmission synchronizer shift fault, a BP neural network prediction method based on genetic algorithm optimization is proposed. The characteristics and defects of BP neural network and genetic algorithm are introduced. Further study the relevant technology combining BP neural net-work and genetic algorithm. The genetic algorithm is used to optimize the weight and threshold of BP neural network, and train the BP neural network prediction model to obtain the optimal solution. The advantages of the local search ability of BP-neural network and global search ability of genetic algorithm are fully displayed. The simulation results show that the method has higher accuracy and better nonlinear fitting ability for transmission synchronizer shift fault.