可靠性分析中的最小二乘支持向量机分类方法

Classification Using Least Squares Support Vector Machine for Reliability Analysis

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.

In order to improve efficiency of support vector machine for classification on dealing with large amount of samples, least squares support vector machine for classification method was intro- duced into the reliability analysis, in which the solving of support vector machine was transformed from a quadratic programming to a group of linear equations to reduce computational cost. The numerical results indicate that the reliability method based on least squares vector for classification has excellent accuracy and a smaller computational cost than support vector machine method.