Table of Contents
International Scholarly Research Notices
Volume 2014, Article ID 358439, 10 pages
Research Article

Intuitionistic Fuzzy Weighted Linear Regression Model with Fuzzy Entropy under Linear Restrictions

1Singhania University, Pacheri Bari, Jhunjhunu, Rajasthan 333515, India
2Jaypee University of Information Technology, Waknaghat 173234, India

Received 18 April 2014; Revised 6 August 2014; Accepted 23 August 2014; Published 30 October 2014

Academic Editor: Bijan Davvaz

Copyright © 2014 Gaurav Kumar and Rakesh Kumar Bajaj. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In fuzzy set theory, it is well known that a triangular fuzzy number can be uniquely determined through its position and entropies. In the present communication, we extend this concept on triangular intuitionistic fuzzy number for its one-to-one correspondence with its position and entropies. Using the concept of fuzzy entropy the estimators of the intuitionistic fuzzy regression coefficients have been estimated in the unrestricted regression model. An intuitionistic fuzzy weighted linear regression (IFWLR) model with some restrictions in the form of prior information has been considered. Further, the estimators of regression coefficients have been obtained with the help of fuzzy entropy for the restricted/unrestricted IFWLR model by assigning some weights in the distance function.