An Interval-Based Approach to Fuzzy Regression for Fuzzy Input-Output Data

被引：0
|
作者：
Chachi, Jalal [1 ]
Taheri, S. Mahmoud [1 ,2 ]
Pazhand, H. Rezaei
机构：
[1] Isfahan Univ Technol, Dept Math Sci, Esfahan 8415683111, Iran
[2] Water Resources & Dam Consulting Engn, Mashhad, Iran
来源：
IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011) | 2011年
关键词：
capability index; fuzzy regression; hydrology; interval arithmetic; least squares method; PROGRAMMING APPROACH; MODEL;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel approach is introduced to construct a fuzzy regression model when the data available of independent and dependent variables are fuzzy numbers. The approach, consisting on the least-squares method, uses the alpha-level sets of fuzzy observations to estimate the crisp parameters of the model. A competitive study shows the performance and efficiency of the proposed approach with respect to some well-known methods.
引用
收藏
页码：2859 / 2863
页数：5
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