Paper Info
Title
Resolution of fuzzy regression model
Abstract
Fuzzy linear regression was originally introduced by Tanaka et al. To cope with different types of input–output information, several approaches to fuzzy linear regression have been proposed. In this paper, a type of problem with crisp input and fuzzy output described by Tanaka is considered of which a modified fuzzy least square method was proposed for solution. It shows that with such an approach the predictability in the new model is better than Tanaka’s and its computation efficiency is better than the conventional fuzzy least square method.
Year
DOI
Venue
2000
10.1016/S0377-2217(99)00317-3
European Journal of Operational Research
Keywords
Field
DocType
Fuzzy regression,Tanaka’s model,Fuzzy least square method,Fuzzy constraint
Mathematical optimization,Defuzzification,Fuzzy classification,Fuzzy set operations,Fuzzy logic,Fuzzy mathematics,Adaptive neuro fuzzy inference system,Fuzzy associative matrix,Fuzzy number,Mathematics
Journal
Volume
Issue
ISSN
126
3
0377-2217
Citations 
PageRank 
References 
24
1.49
5
Authors
2
Name
Order
Citations
PageRank
Hsiao-Fan Wang127827.24
Ruey-chyn Tsaur213812.99