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.

关键词： GM(1,1) model parameter optimization artificial fish swarm algorithm

作者: LIN Zhen-si ZHANG Qi-shan LIU Hong

作者单位: Department of Engineering Management Fujian University of Technology Fuzhou,China School of Management Fuzhou University Fuzhou,China School of Economics and Management Southeast University Nanjing,China

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Grey System and Intelligent Services Joint with the 15th WOSC International Congress on Cybernetics and System(2011 IEEE灰色系统与智能服务国际会议暨系统与控制世界组织第15届年会)

会议地点: 南京

会议语种:英文

页码: 270-274

在线出版日期: 2011-09-15（万方平台首次上网日期，不代表论文的发表时间）