Grey Forecasting Method of Equipment Spare Parts Demand Based on Swarm Intelligence Optimization

In order to improve the precision and efficiency of spare parts demand forecasting, a grey forecasting method of spare parts demand based on swarm intelligence optimization is proposed. On the basis of analyzing the deficiency of the traditional grey prediction method, the fractional grey prediction method is proposed to predict the requirement of spare parts of equipment, this paper presents a swarm intelligence optimization algorithm which combines particle swarm optimization (PSO) and gravity search. By comparison and analysis, this algorithm can quickly and efficiently realize the parameter optimization of fractional grey prediction model, the results show that the fractional grey forecasting model based on swarm intelligence optimization is superior to the traditional grey forecasting model in the precision of fractional grey forecasting.