| 基于粒子群优化的模糊特征自适应选择方法 |
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| 引用本文： | 李林宜,李德仁.基于粒子群优化的模糊特征自适应选择方法[J].测绘学院学报,2011(2). |
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| 作者姓名： | 李林宜 李德仁 |
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| 作者单位： | 武汉大学遥感信息工程学院;武汉大学测绘遥感信息工程国家重点实验室; |
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| 基金项目： | 国家自然科学基金资助项目(41001255); 地理空间信息工程国家测绘局重点实验室经费资助项目(201021); 中央高校基本科研业务费专项资金资助项目(4082007) |
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| 摘 要： | 模糊特征的选择影响着模糊分类的结果。从大量模糊特征中选择出有效特征进行分类,存在着一定的难度。粒子群优化算法(PSO)是基于群体智能的新型进化计算技术,具有自适应、自组织等智能特性,具有强大的寻找最优解的能力。将离散二进制PSO用于模糊特征选择,实现了基于PSO的模糊特征自适应选择方法,并通过航空和卫星遥感影像的模糊分类实验,验证了此方法的有效性。
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| 关 键 词： | 粒子群优化算法 模糊特征选择 模糊分类 自适应 遥感 |
Adaptive Fuzzy Feature Selection Based on Particle Swarm Optimization |
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| LI Lin-yi,LI De-ren.Adaptive Fuzzy Feature Selection Based on Particle Swarm Optimization[J].Journal of Institute of Surveying and Mapping,2011(2). |
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| Authors: | LI Lin-yi LI De-ren |
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| Institution: | LI Lin-yi1,LI De-ren2 (1.School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China,2.State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,China) |
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| Abstract: | Fuzzy feature selection affects fuzzy classification results;however,it is difficult to select effective fuzzy features from large numbers of fuzzy features in fuzzy classification.Particle swarm optimization(PSO) is a new evolutionary computing technique that is based on swarm intelligence.Because of its intelligent properties such as adaptation and self-organizing,PSO has the strong ability to search for the optimal solutions for optimization problems.Discrete binary PSO was used to get the optimal fuzzy ... |
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| Keywords: | particle swarm optimization fuzzy feature selection fuzzy classification adaptive remote sensing |
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