Abstract: In this article, the differential evolution algorithm for the identification of fuzzy systems is offered. On the basis of the offered algorithm five fuzzy systems are constructed, they approximate nonlinear functions from one, two, and three variables. The influence of algorithm parameters on an approximation error is investigated.
Keywords: fuzzy systems, metaheuristics, differential evolution
Authors and copyright holders:
—
For citation:
Hodashinskiy I. A., Dudin P. A. The identification of fuzzy systems based on differential evolution method. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2011, no. 1(23), pp. 178–183.
Last issue
-2025-1.jpg)
Editorial office address
Executive Secretary of the Editor’s Office
Editor’s Office: 40 Lenina Prospect, Tomsk, 634050, Russia
Phone / Fax: + 7 (3822) 701-582
Viktor N. Maslennikov
Executive Secretary of the Editor’s Office
Editor’s Office: 40 Lenina Prospect, Tomsk, 634050, Russia
Phone / Fax: + 7 (3822) 51-21-21 / 51-43-02
Subscription for updates
