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《Computer Technology and Development》 2013-07
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Data Mining Algorithm Based on RBF Neural Network and Rough Sets

CHU Bing,WU Chen,YANG Xi-bei(College of Computer Science and Engineering,Jiangsu University of Science and Technology, Zhenjiang 212003,China)  
With the rise of data mining technology,in order to improve the accuracy of data mining,a lot of data mining algorithms have been put forward.The data mining algorithm which combinesneural networks with rough set theory has been one of the hot spots of data mining research based on rough set theory.Put forward the new idea of training data firstly,then pass to rough sets data mining after eliminating interference data,take the advantages of Radical Basis Function(RBF) neural network:fast convergence rate and strong generalization capability etc.And through the contrast to the data mining results which not using RBF neural network training,the precision of the algorithm which combined RBF neural network with rough set is greatly improved,it shows that the data mining algorithm which combined with neural network and rough sets theory has validity and feasibility.
【Fund】: 国家自然科学基金资助项目(61100116/F020512)
【CateGory Index】: TP183;TP311.13
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