直觉模糊最小二乘支持向量机

J4 ›› 2012, Vol. 50 ›› Issue (05): 993-997.

直觉模糊最小二乘支持向量机

郭新辰, 张超, 李成龙

东北电力大学理学院, 吉林吉林 132012

收稿日期:2012-05-21 出版日期:2012-09-26 发布日期:2012-09-29
通讯作者: 郭新辰 E-mail:neduer@163.com

Intuitionistic Fuzzy Least Square Support Vector Machine

GUO Xinchen, ZHANG Chao, LI Chenglong

College of Science, Northeast Dianli University, Jilin 132012, Jilin Province, China

Received:2012-05-21 Online:2012-09-26 Published:2012-09-29
Contact: GUO Xinchen E-mail:neduer@163.com

摘要/Abstract

摘要：

将直觉模糊集的相关理论引入到最小二乘支持向量机中, 建立了直觉模糊最小二乘支持向量机的数学模型, 并对模型的求解过程进行推导. 为验证该算法的有效性, 在人工数据集和标准数据集上进行仿真实验. 实验结果表明, 直觉模糊最小二乘支持向量机算法可降低分类时样本中噪声和野点对分类效果的影响.

关键词: 直觉模糊；最小二乘支持向量机；分类

Abstract:

By means of the introduction of intuitionistic fuzzy set theory into the least squares support vector machine, the mathematical model of the intuitionistic fuzzy least squares support vector machine was established, and the solution to the model was derived. The simulation experiments were performed on both artificial data sets and benchmark data sets to verify the effectiveness of the proposed algorithm. The results show that the intuitionistic fuzzy least squares support vector machine algorithm can reduce the serious impact of sample noise and outliers on classification effect.

Key words: intuitionistic fuzzy, least squares support vector machine, classification

中图分类号:

TP181

郭新辰, 张超, 李成龙. 直觉模糊最小二乘支持向量机[J]. J4, 2012, 50(05): 993-997.

GUO Xin-Chen, ZHANG Chao, LI Cheng-Long. Intuitionistic Fuzzy Least Square Support Vector Machine[J]. J4, 2012, 50(05): 993-997.