TY - JOUR
ID - 678780
TI - Ishita Approach to Construct an Intuitionistic Fuzzy Linear Regression Model
JO - Fuzzy Optimization and Modeling Journal
JA - FOMJ
LA - en
SN -
AU - Al-Qudaimi, Abdullah
AD - Hodeidah University
Y1 - 2021
PY - 2021
VL - 3
IS - 1
SP - 1
EP - 11
KW - Atanassovâ€™s triangular intuitionistic fuzzy number (ATIFN)
KW - Intuitionistic fuzzy linear regression
KW - Least absolute deviations
DO - 10.30495/fomj.2021.678780
N2 - To the best of our knowledge, there is only two approaches for constructing an intuitionistic fuzzy linear regression model (regression model in which all the variables and coefficients are considered as intuitionistic triangular fuzzy numbers). However, after a deep study, some mathematical incorrect assumptions have been considered in these approaches. Therefore, it is scientifically incorrect to use these approaches for general real-life data. Keeping the same in mind, in this paper, a new approach (named as Ishita approach) is proposed to construct an intuitionistic fuzzy linear regression model. The proposed approach overcomes the limitations of the existing approaches. It is fit for positive, negative or mixed of positive and negative datasets represented as symmetric or asymmetric intuitionistic triangular fuzzy numbers. Moreover, the constructed models of the proposed approach guarantee the homogeneity principle such that for symmetric intuitionistic fuzzy data, the constructed model is symmetric, i.e., the estimated modelâ€™s coefficients are symmetric intuitionistic fuzzy numbers. Furthermore, the proposed approach is illustrated with the help of a numerical example.
UR - http://fomj.qaemiau.ac.ir/article_678780.html
L1 - http://fomj.qaemiau.ac.ir/article_678780_d8eb10ec955e596f0776d9b061e4b8ba.pdf
ER -