Parameter optimization of GM(1,1) model based on artificial fish Swarm algorithm

摘要

There are many methods to improve the accuracy of GM(1,1) model and the Swarm intelligent algorithms can be used to optimize the development coefficient and grey action quantity of GM(1,1) model effectively. In this paper, an optimization GM(1,1) model about identifying the parameters is proposed, which takes the minimum of the average relative error as the objective function. Moreover, an improved artificial fish swarm algorithm is designed to solve the optimization model. The simulation results show that the proposed method may enhance the precision of GM(1,1) model, which has a better performance than Particle Swarm Optimization.