[1]严华雯 吴健平.加权最小二乘法改进遗传克里金插值方法研究[J].计算机技术与发展,2012,(03):92-95.
　YAN Hua-wen,WU Jian-ping.Research on Genetic Algorithm Kriging Optimized by Weight Least Square[J].,2012,(03):92-95.
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加权最小二乘法改进遗传克里金插值方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年03期
页码:
92-95
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Research on Genetic Algorithm Kriging Optimized by Weight Least Square
文章编号:
1673-629X（2012）03-0092-04
作者:
严华雯 吴健平
华东师范大学地理信息科学教育部重点实验室
Author(s):
YAN Hua-wen; WU Jian-ping
Ministry of Education Key Lab of Geographic Information Science,East China Normal University
关键词:
克里金; 遗传算法; 变异函数; 加权最小二乘法
Keywords:
Kriging;  genetic algorithm;  semi-variogram;  weight least square
分类号:
TP311.52
文献标志码:
A
摘要:
数据内插被广泛应用于地统计分析领域,克里金插值作为其中最为有效的方法之一,其原理是通过建立变异函数理论模型,得到可靠的权重值和拉格朗日系数,构成求解待测点的线性组合。为了有效地提高插值精度,文中利用加权最小二乘法优化遗传算法中的适应度函数,进而改进普通基于遗传算法优化的克里金插值方法。并且在MATLAB中利用外部工具箱确定模型参数,最后通过实例验证,将该方法与普通克里金插值以及遗传克里金插值结果进行对比,发现采用该方法,插值效果较好且误差也较小,证明了通过加权最小二乘法可以有效改进普通遗传克里金插值方法
Abstract:
Data interpolation is widely used in the field of geostatistical analysis.As one of the most effective methods of data interpolation,using Kriging could obtain reliable weight values to build up the linear combination by means of the establishment of semi-variogram model.In order to improve the accuracy of interpolation,weight least square is used in this paper to optimize the fitness function in genetic algorithm,then improve Kriging optimized by genetic algorithm only.Model parameters can be calculated by toolbox in MATLAB.Finally,verified by example data and compared with ordinary Kriging and genetic algorithm Kriging,this method is found to achieve a more interpolation result and get less error.Weight least square is proved to be an effective method to improve ordinary genetic algorithm Kriging

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备注/Memo

备注/Memo:
国家重点基础研究发展计划（973计划）项目（2010CB951603）严华雯（1987-），女，上海人，硕士研究生，CCF会员，研究方向为GIS应用与开发；吴健平，博士，教授，博导，主要研究方向为GIS应用与开发
更新日期/Last Update: 1900-01-01