Open AccessApplication of the theory of fuzzy sets for a qualitative analysis of mathematical models
Author(s) -
Dilnoz Muhamediyeva
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1546/1/012091
Subject(s) - fuzzy logic , least squares function approximation , sample (material) , computer science , estimation , mathematics , mathematical optimization , fuzzy number , fuzzy set , algorithm , statistics , artificial intelligence , engineering , chemistry , systems engineering , chromatography , estimator
The article discusses the estimation of fuzzy regression parameters when specifying various membership functions, since the effectiveness of the least squares method dramatically reduces when a number of prerequisites for its use are violated, in particular, when the sample being processed contains observations that are poorly consistent with the others. In these cases, one can use estimation methods that are less sensitive than the least squares method to specification errors and allow one to obtain so-called fuzzy estimates. Among such methods is the method of smallest modules, the implementation of which leads to the problem of linear programming.