Title : ( Fuzzy Regression Model With Interval-Valued Fuzzy Input-Output Data )
Authors: Mohammadreza Rabiei , ناصر رضا ارقامی , سید محمود طاهری , Bahram Sadeghpour Gildeh ,
Full TextAbstract
A novel approach is introduced to construct a fuzzy regression model when both input data and output data are interval-valued fuzzy numbers. Using a distance on the space of interval-valued fuzzy numbers, a least-squares method is developed. Also, a nonlinear programming model is proposed to estimate the crisp parameters for the interval-valued fuzzy regression model. A real example demonstrates the feasibility and efficiency of the proposed method. Moreover, two goodness of fit indices are introduced and employed for more evaluation of such fuzzy interval-valued regression models.
Keywords
, Interval-valued fuzzy number, fuzzy regression, least-squares method, goodness of fit
@inproceedings{paperid:1038979,
author = {Rabiei, Mohammadreza and ناصر رضا ارقامی and سید محمود طاهری and Sadeghpour Gildeh, Bahram},
title = {Fuzzy Regression Model With Interval-Valued Fuzzy Input-Output Data},
booktitle = {(The 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013},
year = {2013},
location = {Hyderabad, IRAN},
keywords = {Interval-valued fuzzy number; fuzzy regression; least-squares method; goodness of fit},
}
%0 Conference Proceedings
%T Fuzzy Regression Model With Interval-Valued Fuzzy Input-Output Data
%A Rabiei, Mohammadreza
%A ناصر رضا ارقامی
%A سید محمود طاهری
%A Sadeghpour Gildeh, Bahram
%J (The 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013
%D 2013
