Telephone Traffic Forecasting Based on Grey Neural Network Optimized by Improved Particle Swarm Optimization Algorithm

Abstract

To solve the problem that the parameters in grey neural network (GNN) are difficult to determine, the improved Particle Swarm Optimization (IPSO) algorithm is employed to search the optimums by the introduction of a threshold of velocity. When the particle velocity is less than the threshold, an accelerated momentum is applied on the particle to reinitialize the particle velocity and position. The proposed approach is used to predict the telephone traffic of two regions. The forecasting results are compared with those of GNN, Grey Neural Network optimized by Particle Swarm Optimization (PSO-GNN) and Back-Propagation Neural Network (BPNN). The experimental results show high prediction accuracy.