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《Journal of Zhejiang University(Science Edition)》 2011-03
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Application of radial basis function neural networks to prospectivity mapping for gold deposits in Southeastern Yunnan,China

BAI Jian1,2,YU Le3,4(1.School of Geoscience and Resources,China University of Geoscience,Beijing 100083,China;2.Yunnan Bureau of Geology and Mineral Resources,Kunming 650011,China;3.Department of Earth Sciencs,Zhejiang University,Hangzhou 310027,China;4.Center for Earth System Science,Tsinghua University,Beijing 100084,China)  
The use of artificial neural network(ANN) helps to understand ore-forming system of the nonlinear dynamical behaviors and prediction of mineral resources.RBFNN(Radial Basis Function Neural Network,RBFNN) has excellenl approximation property.Its optimizing process is simple,training process is fast,which suitable for the needs of integrating huge numbers of data together for mineral prospectivity mapping.In this paper,RBFNN model is employed to gold prospectivity mapping in Southeastern Yunnan,China.The experimental results show that the model can quickly obtain the information of patentiality of gold deposits.ROC(receiver operating characteristic) curve shows the accuracy of this model is excellent.
【CateGory Index】: P618.51
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