TY - JOUR
ID - 230
TI - FUZZY LINEAR REGRESSION BASED ON
LEAST ABSOLUTES DEVIATIONS
JO - Iranian Journal of Fuzzy Systems
JA - IJFS
LA - en
SN - 1735-0654
AU - Taheri, S. M.
AU - Kelkinnama, M.
AD - Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran and Department of Statistics, School of Mathematical
Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
AD - Department of Mathematical Sciences, Isfahan University of Technology, Isfahan 84156-83111, Iran
Y1 - 2012
PY - 2012
VL - 9
IS - 1
SP - 121
EP - 140
KW - Fuzzy regression
KW - Least absolutes deviations
KW - Metric on fuzzy numbers
KW - Similarity measure
KW - Goodness of fit
DO - 10.22111/ijfs.2012.230
N2 - This study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. A least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. The proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by three goodness of t criteria. Three well-known data sets including two small data sets as well as a large data set are employed for such comparisons.
UR - https://ijfs.usb.ac.ir/article_230.html
L1 - https://ijfs.usb.ac.ir/article_230_d59e96e289e06159aecc01cdcd61a9dd.pdf
ER -