Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (1): 79-79.
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YongQuan Zhou,Ming Zhang
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张明,周永权
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Abstract: In this paper, function fitting can be considered as optimal search processes of model structures and parameters. A new genetic programming modeling method, combining evolution strategy, was proposed for hybrid identification of model structure and model parameters by performing global optimal search in the complex solution space where the structures and parameters coexist and interact. The method which determining the structures of the function and solving parameter at the same time conquer the traditional disadvantage which rely on data, lower precision and determining the structures first and solving parameters. Application results proved the high precision and generalization capacity of the fitting function model obtained by the new method.
Key words: genetic programming, evolution strategy, function fitting, least square error, square deviation
摘要: 文中把函数拟合建模看作是模型结构和参数的优化搜索过程,将遗传规划和进化策略结合起来对函数拟合的结构和参数共存且相互影响的复杂解空间进行全局最优搜索实现拟合结构和参数的共同识别. 克服了传统的函数拟合完全依赖于数据、精度低、结构与参数分别确定这样一“串行”计算结构等缺陷. 实验数据表明,该方法得到的拟合函数比传统方法得到的拟合函数,具有较高的精度和推广预测能力.
关键词: 遗传规划, 进化策略, 函数拟合, 最小二乘误差, 均方差
YongQuan Zhou,Ming Zhang. Application of Genetic Programming and Evolution Strategy Algorithm in Fitting Function[J]. Computer Engineering and Applications, 2007, 43(1): 79-79.
张明,周永权. 遗传规划和进化策略混合算法及应用[J]. 计算机工程与应用, 2007, 43(1): 79-79.
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