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计算机工程 ›› 2011, Vol. 37 ›› Issue (14): 155-157. doi: 10.3969/j.issn.1000-3428.2011.14.051

• 人工智能及识别技术 • 上一篇    下一篇

基于PSO算法的变差函数球状模型参数拟合

梁昔明,肖晓芳   

  1. (中南大学信息科学与工程学院,长沙 410083)
  • 收稿日期:2011-02-24 出版日期:2011-07-20 发布日期:2011-07-20
  • 作者简介:梁昔明(1967-),男,教授、博士生导师,主研方向:智能计算,进化计算;肖晓芳(通讯作者),硕士研究生
  • 基金资助:
    国家自然科学基金资助项目(60874070);中南大学研究生学位论文创新基金资助项目“过程控制系统设定点全局优化的粒子群算法研究”(2009ssxt190)

Parameter Fitting of Variogram Spherical Model Based on Particle Swarm Optimization Algorithm

LIANG Xi-ming, XIAO Xiao-fang   

  1. (School of Information Science and Engineering, Central South University, Changsha 410083, China)
  • Received:2011-02-24 Online:2011-07-20 Published:2011-07-20

摘要: 对一阶变差函数球状模型及其二阶套合结构的参数拟合进行研究,利用粒子群优化(PSO)算法在求解非线性优化问题时收敛的快速性以及全局寻优的有效性等优势,将待拟合球状模型的参数组合为一个粒子向量,在PSO算法迭代过程中对部分粒子进行混合柯西-高斯变异,实现变差函数球状模型最优参数的自动拟合。仿真实验结果表明,该方法操作简单、可靠性高。

关键词: 粒子群优化算法, 变差函数, 球状模型, 参数拟合

Abstract: This paper researches the regression of the first spherical model and its mugget structure of theoretic variogram, and takes advantages of the Particle Swarm Optimization(PSO) algorithm which has outstanding advantages in solving nonlinear optimization problems for the rapid convergence and the effectiveness of global optimization. Its combination of the parameters in the spherical model are considered as a vector, during the interation of PSO algorithm, and mixed Cauchy-Gaussian mutation is carried out on part of the particles. The automtic regression of the spherical model is achieved. Simulation results show that this method is simple and has high reliability.

Key words: Particle Swarm Optimization(PSO) algorithm, variogram, spherical model, parameter fitting

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