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《Science of Surveying and Mapping》 2010-01
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Visual classification prediction method for nonlinear and multi-dimensional data

LI Zhi-jian,ZHENG Xin-qi,ZHAO Lu,YANG Xin(School of Land science and Technology,China University of Geosciences,Beijing 100083,China)  
Traditional linear classification algorithms of GIS have the advantage of determining in positive direction quickly,but have the limitation in determining the given data linearly.However,the classification prediction for the unknown non-linear information is the important part of GIS.Artificial neural network algorithm makes it possible to discover some non-linear knowledge.Based on the common format of GIS data,the paper adopted L-M algorithm to do classification and to classify and predict the unknown information further through the classification results.A neural network classification prediction visualization module based on GIS was constructed,which was tested using the U.S.towns and population data.It is proved that the L-M algorithm is feasible and the module is of practicality.
【Fund】: 国家自然科学基金项目(编号:40571119);; 国家社会科学基金项目(07BZZ015);; 国家科技支撑项目资助课题(2006BAB15B03 2006BAB15B06);; 中国地质大学(北京)人才基金资助项目(51900912300)
【CateGory Index】: TP391.41
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