基于PSO的非线性马斯京根模型参数率定新方法  

Parameter Estimation Method of Nonlinear Muskingum Model Based on PSO

作　　者：马细霞[1] 舒丹丹[1] 黄渝桂[1] 

机构地区：[1]郑州大学环境与水利学院,河南郑州450001

出　　处：《郑州大学学报（工学版）》2007年第4期122-125,共4页Journal of Zhengzhou University（Engineering Science）

基　　金：河南省自然科学基金资助项目(0411050800);河南省杰出青年科学基金资助项目(512002500)

摘　　要：针对目前马斯京根河道洪水演进模型参数率定中所存在的线性化、求解复杂、精度差等问题,本文提出了一种基于粒子群优化(Particle Swarm Optimization,PSO)算法的非线性马斯京根模型参数率定新方法,并将其应用于称钩弯—临清段洪水演进计算中.通过与PSO线性模型、最小二乘法线性模型参数率定法洪水演算结果的对比分析,发现基于PSO算法的非线性模型精度高于两种线性模型,1960、1961和1964年三场典型洪水误差平方和分别减小了0.9%、6.2%和1.6%,表明基于PSO的非线性马斯京根模型参数率定结果更接近实际洪水的演进过程.A new algorithm,parameter estimation for nonlinear Muskingum model based on Particle Swarm Optimization （PSO） is proposed in this paper in order to solve the problem of linearization,complexity and poor accuracy for parameter estimation of Muskingum model at present. And the new method is applied in the river flood routing of Chenggouwan to Linqing. According to the comparison with PSO linear model and liner least square method in the parameter rating, it is found that the nonlinear POS model has higher accuracy than the two other models , and the sum of the square errors of the three typical floods in 1960,1961,1964 are reduced respectively by 0.9% ,6.2%. 1.6%. It shows that the result of nonlinear parameter rating model based on PSO is closer to the actual result of the evolution of the floods.

关 键 词：非线性马斯京根模型 粒子群优化算法 中心距离函数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]