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《Journal of China Coal Society》 2006-02
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Application of self-organizing mapping artificial neural networks compared with hierarchical clustering analyses in sedimentary type analysis

GE Xiao-guang,WU Xiao,QIAN Kai (School of Resources and Environment Engineering,Hefei University of Technology,Hefei 230009,China)  
Both SOM(Self-Organizing Mapping) network and hierarchical clustering(HC) methods were tried to classify 19 soil samples from Sunan mining district and near regions for the Neocene sediment type recognition in Huaibei coalfield.It is found that the results of SOM are fit for the known types closer than those of HC.The function differences between the two methods were discussed on their mechanism and applied ways.SOM is proved to be more convenient in classifying applications,and to be able to identify incomplete samples in a unique result without any prior knowledge.
【CateGory Index】: P512.2
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