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《Scientific and Technological Management of Land and Resources》 2012-06
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Method of Kernel Principal Component Regression and Its Application

CHEN Yong-liang1,LU Lai-jun2(1.Institute of Mineral Resources Prognosis on Synthetic Information,Jilin University,Changchun 130026,China;2.College of Earth Sciences,Jilin University,Changchun 130061,China)  
A method for mineral target prediction is proposed based on kernel principal component regression.On the basis of GDAL digital image input and output function library and kernel principal component regression,VC++ program is applied to develop a digital image data oriented mineral target prediction with kernel principal component regression model,and an experiment on the application of the new model is conducted in Altay of northern Xinjiang.The result shows that the statistical cells with high ore-bearing possibilities spatially coincide with the known ore-deposits.It is concluded that kernel principal component regression is feasible for mineral target prediction.
【Fund】: 国家自然科学基金(40872193 41072244 41272360);; 吉林大学种子基金(450060481313)
【CateGory Index】: P612
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【Citations】
Chinese Journal Full-text Database 2 Hits
1 CHEN Yong-liang,LIN Nan,LI Xue-bin Institute of Mineral Resources Prognosis Synthetic Information,Jilin University,Changchun 130026,China;Lanczos Algorithm for Kernel Principle Component Analysis on Large Scale Samples[J];Journal of Jilin University(Earth Science Edition);2010-01
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【Co-citations】
Chinese Journal Full-text Database 5 Hits
1 CHEN Yong-liang,LI Xue-bin Mineral Resources Institute of Comprehensive Information Prediction,Jilin University,Changchun 130026,China;Mineral Target Prediction Based on Kernel Minimum Square Error[J];Journal of Jilin University(Earth Science Edition);2011-03
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