TY - JOUR
ID - 322
TI - ESTIMATING THE PARAMETERS OF A FUZZY LINEAR
REGRESSION MODEL
JO - Iranian Journal of Fuzzy Systems
JA - IJFS
LA - en
SN - 1735-0654
AU - Arabpour, A. R.
AU - Tata, M.
AD - Faculty of Mathematics and Computer Sciences, Shahid Bahonar
University of Kerman, Kerman, Iran
AD - Faculty of Mathematics and Computer Sciences, Shahid Bahonar University
of Kerman, Kerman, Iran
Y1 - 2008
PY - 2008
VL - 5
IS - 2
SP - 1
EP - 19
KW - Fuzzy linear regression
KW - Least squares method
KW - Estimate
DO - 10.22111/ijfs.2008.322
N2 - Fuzzy linear regression models are used to obtain an appropriate
linear relation between a dependent variable and several independent variables
in a fuzzy environment. Several methods for evaluating fuzzy coefficients in
linear regression models have been proposed. The first attempts at estimating
the parameters of a fuzzy regression model used mathematical programming
methods. In this thesis, we generalize the metric defined by Diamond and
use it as a criterion to estimate these parameters. Our method, is not only
computationally easy to handle, but, when compared with earlier methods,
has a smaller the sum of errors of estimation.
UR - https://ijfs.usb.ac.ir/article_322.html
L1 - https://ijfs.usb.ac.ir/article_322_89ab18dcd4fa63d8116aaf289ebdb6b0.pdf
ER -