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《Acta Simulata Systematica Sinica》 2005-01
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Study on the Support Vector Machines Model for Sales Volume Prediction and Parameters Selection

WEI Hong-ye, WANG Jian-hua, HE Wei(China United Telecommunications Corporation Beijing Branch, Beijing 100038, China;School of International Economics and Management, Lanzhou University of Technologies, Lanzhou 730050, China; China Aerospace Science and Technology Corporation, Beijing 100854, China)  
Support vector machine is a learning technique based on the structural risk minimization principle, and it is also a class of regression method with good generalization ability. Support vector machine is used to model enterprise sale amount prediction, and the theory of SVR are briefly described. A simulation example is taken to demonstrate correctness and effectiveness of the proposed approach. The selection method of the model parameters is presented.
【Fund】: 国家自然基金资助项目(60172063) 教育部博士点基金项目(20010004004)
【CateGory Index】: F224
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