Prediction of electromagnetic interference based on neural network

A method to predict the electromagnetic interference using neural network was proposed. Genetic algorithm has the strong overall search ability but easy to fall into local optimum, and simulated annealing algorithm has the partial search ability, avoiding the search into local optimal solution. By using the simulated annealing algorithm and genetic algorithm combining, the back propagation (BP) neural network weights and thresholds were optimized, and the number of hidden layer neurons was determined by the simulated annealing ideas. Then, the neural network-based predictive models of electromagnetic interference was established. With the two parallel leads to electromagnetic interference matter as predicted instance, interference factors were identified, and the training and test samples were established. In contrast to the error between the expected output and the predicted output, the results show that the method can accurately predict the electromagnetic interference effectively.