Predicting Short-Term Orders by an Improved Grey Neural Network Model

Abstract

According to the validation that the random selection of the gray neural network parameters random selection is similar to initial the space position of the particle in the particle swarm algorithm, the gray neural network based on the modified particle swarm optimization (PSO) algorithm is established to improve the robustness and the precision of the net model with applying a improved PSO algorithm to instead of gradient correction method, updating the network parameter and searching the best individual in this algorithm. There are several methods to forecast the short-term orders, including BP, the gray network, the original PSO algorithm and the improved PSO algorithm. Comparing with these methods, the results demonstrated the grey network based on the improved PSO algorithm has better approximation ability and prediction accuracy.