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《Science of Surveying and Mapping》 2007-02
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The application and research progress of SVM in spatial information processing

TAN Kun,DU Pei-jun,ZHENG Hui(Department of Remote Sensing and Geographical Information Science,China University of Mining and Technology,Xuzhou 221008,China;Yanzhou Mining Bureau JiShan Coal Mine,Jining 272043,China)  
As one of the most popular and effective statistical learning algorithm,Support Vector Machine(SVM)has become a new hot topic in pattern recognition and machine learning fields in recent years.SVM has some advantages,for example,its applicability to limited samples,robustness to noises,high learning efficiency and easy generalization,and those are commonly difficult issues in spatial information processing.So SVM can be used to spatial information processing,and some major applications include RS image processing,hyper-spectral RS data classification,spatial approximation and regression,data mining,target identification,and so on.Based on a brief introduction and summary to the achievements of SVM used to spatial information processing,some potential applications,including spatial data mining,intelligent spatial information process and high-dimensional spatial data processing are discussed in detail.
【Fund】: 国家自然科学基金项目(40401038);; 测绘遥感信息工程国家重点实验开放基金项目(2004重点项目第三子课题);; 中国矿业大学科学基金资助项目(D200403)
【CateGory Index】: TP18;TP311.13
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