摘要
采用灰色系统理论,建立了基于GM(1,1)的船闸货运量预测模型.模型参数计算分别采用粒子群优化算法和最小二乘法,两者进行对比发现,预测误差相当,但是粒子群优化算法可以避免繁琐的矩阵运算而优于最小二乘法.应用基于粒子群优化算法的灰色系统模型进行了船闸货运量的预测.
Based on the grey system theory,the GM（1,1） forecast model of the lock freight volume is established.The particle swarm optimization and the least square method are adopted respectively to compute the model parameters.Consequent results are analyzed and compared,which shows the particle swarm optimization is better than the least square method.The future lock freight volume is predicted by using the model and the grey forecast method based particle swarm optimization is recommended to be used in the waterway engineering.
出处
《武汉理工大学学报（交通科学与工程版）》
2011年第6期1135-1138,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目资助(批准号:50479032)
关键词
粒子群优化
灰色理论
船闸
货运量
预测模型
particle swarm optimization
grey theory
lock
freight volume
forecast model
