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›› 2002, Vol. 28 ›› Issue (08): 36-38.

• 论文 • 上一篇    下一篇

基于SVM的综合评价方法研究

肖健华,吴今培,杨叔子   

  1. 华中科技大学机械科学与工程学,五邑大学智能技术与系统研究所,华中科技大学机械科学与工程学 武汉 430074五邑大学智能技术与系统研究所江门 529020
  • 发布日期:2002-08-25

Approach of Evaluation System Based on Support Vector Machine

XIAO Jianhua1,2,WU Jinpei2,YANG Shuzi1   

  1. (1. School of Mechanics, Huazhong University of Science & Technology, Wuhan 4300742.Institute of Intelligence Technology & Systems, Wuyi University,Jiangmen 529020)
  • Published:2002-08-25

摘要: 系统介绍了统计学习理论与支持向量机的基本思想,研究了它们在综合评价中的应用。分析了科研立项评审系统的设计方法,建立了基于的评审系统。文末比较了新评审系统和采用其它方法如模糊排序、神经网络等建立的评审系统所分别取得的拟合效果,比较结果SVM表明:采用支持向量机设计的评审系统结构简单、思路清晰且能取得更为理想的评审结果。

关键词: 支持向量机, 统计学习理论, 综合评价

Abstract: In this paper,the basic theory of statistical learning theory(SLT) and support vector machine(SVM)are introduced systemically and the application of SLT and SVM in the evaluation system are studied.For example, the design method of evaluation system for research projects supported by science foundation is analyzed.In order to improve the generalization performance,it reconstructs the evaluation system based on SVM.At the end of the paper,the comparison of the result of simulation between the evaluationsystem based on SVM and that based on other methods such as neural network and fuzzy sorting are discussed. The result shows that an ideal classification result can be acquired by adoption of SVM in this evaluation process. ;;

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