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可靠性分析中的最小二乘支持向量机分类方法

郭秩维 白广忱

郭秩维, 白广忱. 可靠性分析中的最小二乘支持向量机分类方法[J]. 应用数学和力学, 2009, 30(7): 799-810. doi: 10.3879/j.issn.1000-0887.2009.07.005
引用本文: 郭秩维, 白广忱. 可靠性分析中的最小二乘支持向量机分类方法[J]. 应用数学和力学, 2009, 30(7): 799-810. doi: 10.3879/j.issn.1000-0887.2009.07.005
GUO Zhi-wei, BAI Guang-chen. Classification Using Least Squares Support Vector Machine for Reliability Analysis[J]. Applied Mathematics and Mechanics, 2009, 30(7): 799-810. doi: 10.3879/j.issn.1000-0887.2009.07.005
Citation: GUO Zhi-wei, BAI Guang-chen. Classification Using Least Squares Support Vector Machine for Reliability Analysis[J]. Applied Mathematics and Mechanics, 2009, 30(7): 799-810. doi: 10.3879/j.issn.1000-0887.2009.07.005

可靠性分析中的最小二乘支持向量机分类方法

doi: 10.3879/j.issn.1000-0887.2009.07.005
基金项目: 国家高技术研究发展计划(863)资助项目(2006AA04Z405)
详细信息
    作者简介:

    郭秩维(1981- ),男,山东人,博士生(联系人.Tel:+86-10-83929385;E-mail:guozhiwei-guoshuai@vip.sina.com).

  • 中图分类号: TB114.3

Classification Using Least Squares Support Vector Machine for Reliability Analysis

  • 摘要: 为了提高支持向量分类机在处理大样本可靠性问题时的计算效率,将最小二乘支持向量分类机引入到可靠性分析中,使得支持向量机中的二次规划问题转化为求解线性方程组问题,减少了计算量.数值算例表明:基于最小二乘支持向量分类机的可靠性方法与基于支持向量分类机的可靠性方法具有一样的计算精度,而且前者的计算效率明显优于后者.
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出版历程
  • 收稿日期:  2008-05-19
  • 修回日期:  2009-05-18
  • 刊出日期:  2009-07-15

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