Support vector fuzzy regression machines

被引：108

作者：

Hong, DH

Hwang, CH

机构：

[1] Catholic Univ Daegu, Sch Mech & Automat Engn, Kyongsan 712702, Kyungbuk, South Korea

[2] Catholic Univ Daegu, Dept Stat Informat, Kyungbuk 712702, South Korea

来源：

FUZZY SETS AND SYSTEMS | 2003年 / 138卷 / 02期

关键词：

fuzzy inference systems; support vector machine; fuzzy regression; fuzzy system models;

D O I：

10.1016/S0165-0114(02)00514-6

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems. In this paper, we introduce the use of SVM for multivariate fuzzy linear and nonlinear regression models. Using the basic idea underlying SVM for multivariate fuzzy regressions gives computational efficiency of getting solutions. (C) 2002 Elsevier B.V. All rights reserved.

引用

页码：271 / 281

页数：11

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