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《Journal of Shanghai Jiaotong University》 2007-12
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A Frost Growth Characteristics Predication Model Based on Support Vector Machine

REN Neng,GU Bo(Inst.of Refrigeration and Cryogenics Eng.,Shanghai Jiaotong Univ.,Shanghai 200240,China)  
Frost growth was a strong nonlinear and time-varying process,and the experimental data was(usually) interfered by noise;so it was hardly to predict its characteristics precisely.In order to solve this problem,a learning method support vector machine(SVM) which is based on the structure risk minimization principle was introduced;then a set of thermal parameters,time and space coordinates were selected;finally the predication models of frost growth characteristics were presented based on those characteristic vectors.The predicated results were verified by the experimental data,which shows a good agreement.Comparing SVM predication model with LS predication model shows that the SVM model has better ability to deal with nonlinear and noise interference problems.
【Fund】: 国家重点基础研究发展规划(973)项目(G2000026309)
【CateGory Index】: TB61
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【References】
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1 CAO Zhi-kun~1,GU Bo~1,GU Zhong~2(1.School of Mechanical Engineering,Shanghai Jiaotong University,Shanghai 200240,China;2.Carrier China R & D Ltd.,Shanghai 201206,China);Optimization Model of Refrigerated Display Cabinet Based on Modified Support Vector Machine[J];Journal of Shanghai Jiaotong University;2009-09
【Citations】
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【Co-citations】
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1 ZHAO Qun-li,JIAO He-jun (Department of Computer Science & Engineering,Henan Institute of Engineering,Zhengzhou 451191,China);Research of Resource Optimal Configuration for Networked Manufacturing[J];Equipment Manufacturing Technology;2009-10
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3 LIU Mei1,2,CHEN Zheng-shi1,SUN Zong-hai2(1.Department of Automation,Maoming University,Maoming Guangdong 525000,China;2.College of Automation Science and Technology,South China University of Technology,Guangzhou Guangdong 510640,China);Prediction of Melt Index Based on Wavelet and LS-SVM[J];Computer Simulation;2009-10
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