TY - JOUR T1 - Heuristic Approches to Fuzzy Regression TT - رویکردهای ابتکاری در رگرسیون فازی JF - Andishe-_ye-Amari JO - Andishe-_ye-Amari VL - 22 IS - 2 UR - http://andisheyeamari.irstat.ir/article-1-448-en.html Y1 - 2018 SP - 43 EP - 52 KW - ‎least of sum of errors‎ KW - ‎possibilistic regression‎ KW - ‎heuristic methods‎ KW - ‎clustering‎ KW - ‎variable spreads‎. N2 - ‎There are two main approches to the fuzzy regression (more precisely‎: ‎regression in fuzzy environment)‎: ‎the least of sum of distances (including two methods of least squared errors and least absolute errors) and the possibilistic method (the method of least whole vaguness under some restrictions)‎. ‎Beside‎, ‎some heuristic methods have been proposed to deal with fuzzy regression‎. ‎Some of them are based on a combination of two mentioned approaches‎. ‎Some of them are based on computational algorithmes‎. ‎A few of heuristic methods use the fuzzy inference systems‎. ‎Also‎, ‎there are some methods based on clustering‎, ‎artificial neural networks‎, ‎evolutionary algorithms‎, ‎and nonparametric procedures‎. ‎In this paper‎, ‎a history and basic ideas of the two main approaches to‎ ‎fuzzy regression are reveiwed‎, ‎and some heuristic methods in this topic are investigated‎. ‎Moreover‎, ‎10 criterion are proposed by which one can‎ ‎evaluate and compare fuzzy regression models‎. M3 ER -