| 用遗传算法改进模糊隶属度克里格插值的研究 |
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| 引用本文： | 刘钊,谢颖立.用遗传算法改进模糊隶属度克里格插值的研究[J].测绘科学,2012(4):191-193. |
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| 作者姓名： | 刘钊 谢颖立 |
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| 作者单位： | 清华大学地球空间信息研究所 |
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| 摘 要： | 克里格法是一种应用广泛的空间插值方法,本文研究了指示克里格法和模糊隶属度克里格法,讨论了用遗传算法对模糊隶属度克里格法进行改进的可能性及效果,并在空气污染数据插值中对3种方法的效果进行了比较。实验结果分析表明,遗传算法改进的模糊隶属度克里格插值在结果上要优于前2种方法,且具有鲁棒性较高和适应性较强等优点。
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| 关 键 词： | 克里格法 空间插值 遗传算法 |
Improving fuzzy membership Kriging interpolation with genetic algorithm |
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| LIU Zhao,XIE Ying-li.Improving fuzzy membership Kriging interpolation with genetic algorithm[J].Science of Surveying and Mapping,2012(4):191-193. |
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| Authors: | LIU Zhao XIE Ying-li |
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| Institution: | (Institute of Geospatial Information,Tsinghua University,Beijing 100084,China) |
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| Abstract: | Kriging is a widely used interpolation methods.This paper studied Indicator Kriging method,as well as the Fuzzy Membership Kriging method,and discussed the possibilities of improving the Fuzzy Membership Kriging method with the Genetic Algorithm.At the end,the interpolation results of these three methods were compared in the analysis of air pollution data.The experiments showed that the Genetic Algorithm improved Fuzzy Membership Kriging had better interpolation results than the former two methods,and has higher robustness and adaptability. |
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| Keywords: | Kriging spatial interpolation genetic algorithm |
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