A FUZZY SYSTEM WITH ε-INSENSITIVE LEARNING OF PREMISES AND CONSEQUENCES OF IF-THEN RULES

摘要

First, a fuzzy system based on if-then rules and with parametric consequences is recalled. Then, it is shown that the global and local ε -insensitive learning of the above fuzzy system may be presented as a combination of both an ε -insensitive gradient method and solving a system of linear inequalities. Examples are given of using the introduced method to design fuzzy models of real-life data. Simulation results show an improvement in the generalization ability of a fuzzy system trained by the new method compared with the traditional and other ε -insensitive learning methods.