Analysis of the Methods for Constructing Membership Functions Using Expert Data

Methods for constructing membership functions for one-dimensional numerical fuzzy sets based on expert data are presented. For this purpose, various approaches are used, based on mathematical methods of data approximation. The results of computer experiments are presented. The influence of errors in the data on the constructed membership functions is analyzed.