[1]马细霞,舒丹丹,黄渝桂..基于PSO的非线性马斯京根模型参数率定新方法[J].郑州大学学报(工学版),2007,28(04):122-125.[doi:10.3969/j.issn.1671-6833.2007.04.030]
　Ma Xiaoxia,Shudandane,Huang Yugui.A new method for parameter rate determination of nonlinear Mastingen model based on PSO[J].Journal of Zhengzhou University (Engineering Science),2007,28(04):122-125.[doi:10.3969/j.issn.1671-6833.2007.04.030]

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基于PSO的非线性马斯京根模型参数率定新方法()

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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

28

期数:

2007年04期

页码:

122-125

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

A new method for parameter rate determination of nonlinear Mastingen model based on PSO

作者:

马细霞; 舒丹丹; 黄渝桂.

郑州大学,环境与水利学院,河南,郑州,450001, 郑州大学,环境与水利学院,河南,郑州,450001, 郑州大学,环境与水利学院,河南,郑州,450001

Author(s):

Ma Xiaoxia; Shudandane; Huang Yugui

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

Keywords:

nonlinear Mastingen model;  particle swarm optimization algorithm;  Center distance function

DOI:

10.3969/j.issn.1671-6833.2007.04.030

文献标志码:

A

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.

Abstract:

In view of the problems of linearization, complex solution and poor accuracy in the parameter rate determination of the Mastingen flood evolution model, a new method for parameterization of the Mastingen model based on the Particle Swarm Optimization (PSO) algorithm is proposed, and it is applied to the calculation of flood evolution in the Hook Bend-Linqing section. Through the comparative analysis with the PSO linear model and the least squares linear model parametric rate determination flood calculus, it is found that the accuracy of the nonlinear model based on PSO algorithm is higher than that of the two linear models, and the sum of the squared errors of the three typical floods in 1960, 1961 and 1964 is reduced by 0.9%, 6.2% and 1.6%, respectively, indicating that the parameter rate determination results of the nonlinear Mastingen model based on PSO are closer to the evolution process of actual floods.

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