基于模糊支持向量机的学生抗压能力分析  

Research on Compressive Ability of Students Based on Fuzzy Support Vector Machine

作　　者：石磊[1] 侯丽萍[2] 

机构地区：[1]信阳职业技术学院网络中心 [2]信阳农林学院计算机科学系,河南信阳464000

出　　处：《软件导刊》2014年第8期8-11,共4页Software Guide

基　　金：河南省职业教育教学改革项目(ZJB13180)

摘　　要：抗压能力大小判定是一个多指标、多目标的评价系统,传统计算方法存在繁琐、客观性差的问题。提出了一种改进的模糊支持向量机的评价模型,对抗压能力进行评价。建立模糊隶属度函数,在减少训练集中异常样本点对分类超平面干扰的同时,并没有降低边缘样本点对分类超平面的影响。实验表明,改进的模糊支持向量机提高了抗压能力评价的准确率,模糊支持向量机的泛化能力也得到了提高。To improve students＇ anti pressure ability, make the students can more easily adapt to the society, we need to Understand each student＇s ability level, how to judge the students ability, has been a major research topic. Because the evaluation system to determine the compressive capacity is a multi index, multi object, there is the traditional calculation method is tedious, objectivity poor situation, this paper presents an evaluation of improved fuzzy support vector machine model was evaluated against pressure. In this paper, a fuzzy membership function, reduce thetraining set in abnormal sample point to establish the classification hyper planeinterference at the same time, did not reduce the training set of sam- ple points in the edge of each sample impact on the classification hyperplane. Experiments show that, the improved fuzzy support vector machine to improve the accuracy of compressive capacity evaluation, at the same time, fuzzy support vector machine＇s generalization abilitY has been improved.

关 键 词：模糊支持向量机 抗压能力 隶属度函数 

分 类 号：TP3-0[自动化与计算机技术—计算机科学与技术]