Neural Network Research Using Particle Swarm Optimization

Abstract

In view of the artificial neural network weights training problem, this paper proposed a method to optimize the network's structure parameters and regularization coefficient using two-layer Particle Swarm Optimization (PSO). This algorithm was applied to train Adaline network. Compared with fixed regularization coefficient method and Sliding Mode Variable Structure optimization method, the result showed that it had the advantages of high precision and strong ability of generalization.