遗传算法拟合变异函数的参数

 由于堆积体的空间变异特殊性,用加权多项式回归法进行球状模型的理论变异函数拟合误差很大,有时甚至无法拟合出变异函数.为解决这一问题,结合遗传算法原理,充分利用遗传算法在求解非线性问题时具有全局寻优的特点,拟合出球状模型的理论变异函数参数,并以小湾水电站左岸堆积体边坡的变形监测数据为例进行了计算.经过多方法对实例进行比较分析表明,该方法简便、通用,具有较高的拟合精度,是非线性、不连续可微模型参数估计的好方法.

Genetic algorithm for fitting parameter of variation function

Due to uniqueness of talus slope's spatial variations,the fitting error of the spherical model variation function is bigger using the weighted polynomial regression,sometimes it is impossible to fit variation function.In order to solve this problem,the genetic algorithm is applied to fit the spherical model variational function,because the genetic algorithm is a robust method for search for the optimum solution to the complex problems.The application of genetic algorithm fully exert its advantage on seeking priorities,furthermore,the data of the accumulation body with high slope on the left bank in Front of Xiaowan hydro plant Dam is employed to calculate and test as an example.By comparing and analyzing the dates on the example from different angles,it demonstrates that the new method is convenient,universal and precise.It is an excellent method for estimating parameter of non-liner,incontinuity or differentiable model parameter.