Optimization for Artificial Neural Network with Adaptive inertial weight of particle swarm optimization

Abstract

We present a new method to optimize weights of Artificial Neural Network (ANN) with particle swarm optimization (PSO), also we propose a new selection strategy of inertial weight, which varies according to the training error of artificial neural network, called adaptive inertial weight. By using Adaptive inertial weight, the proposed method can search global optimal solution faster and exactly. The experimental results show that the proposed method is successfully applied to benchmark examples.