Paper Info
Title
Quantile fuzzy regression based on fuzzy outputs and fuzzy parameters
Abstract
A new approach is investigated to the problem of quantile regression modeling based on the fuzzy response variable and the fuzzy parameters. In this approach, we first introduce a loss function between fuzzy numbers which it can present some quantiles of fuzzy data. Then, we fit a quantile regression model between the available data based on proposed loss function. To evaluate the goodness of fit of the optimal quantile fuzzy regression models, we introduce two indices. Inside, we study the application of the proposed approach in modeling some soil characteristics, based on a real data set.
Year
DOI
Venue
2020
10.1007/s00500-019-04424-2
Soft Computing
Keywords
Field
DocType
Fuzzy number, Goodness of fit, Loss function, Fuzzy parameter, Quantile fuzzy regression
Mathematical optimization,Computer science,Soil characteristics,Fuzzy logic,Quantile,Fuzzy regression,Fuzzy number,Fuzzy data,Goodness of fit,Quantile regression
Journal
Volume
Issue
ISSN
24
1
1432-7643
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Mohsen Arefi1243.82