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混沌免疫算法在遥感影像分类中的应用研究
引用本文:武彦斌,黄明.混沌免疫算法在遥感影像分类中的应用研究[J].测绘工程,2007,16(1):55-58.
作者姓名:武彦斌  黄明
作者单位:中国矿业大学,煤炭资源与安全开采国家重点实验室,北京,100083
基金项目:国家“973”资助项目(2002CB211707)
摘    要:为提高遥感影像分类精度,采用基于混沌免疫算法(Chaos Immune Algorithm)的分类方法。利用混沌优化的遍历性,进行粗粒搜索,优化初始抗体群;通过选择算子、克隆算子、变异算子、抗体的循环补充等操作,得到全局最优的聚类中心,提高分类精度。实验表明该方法分类总精度、Kappa系数均优于传统分类方法。

关 键 词:遥感影像分类  混沌  免疫算法
文章编号:1006-7949(2007)01-0055-04
收稿时间:2006-12-08
修稿时间:2006年12月8日

Remote sensing image classification based on chaos immune algorithm
WU Yan-bin,HUANG Ming.Remote sensing image classification based on chaos immune algorithm[J].Engineering of Surveying and Mapping,2007,16(1):55-58.
Authors:WU Yan-bin  HUANG Ming
Affiliation:National Laboratory of Coal Resources and Mine Safety, CU M TB, Beijing 100083, China
Abstract:To improve the accuracy of remote sensing image classification,chaos immune glgorithm is proposed.The ergodic property of chaos phenomenon is used to optimize the initial antibody population,in order to accelerate the convergence of immune algorithm.Through the adjusted antibody affinity,selection operator is formed.By the selection operator,clone operator,mutation operator and recruited antibody,local optimums are avoid.It is demonstrated that chaos immune algorithm is superior to the two traditional algorithms,and its overall accuracy and Kappa coefficient reach 89.8% and 0.8725respectively.
Keywords:remote sensing image classification  chaos  immune algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
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