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JOURNALS // Artificial Intelligence and Decision Making // Archive

Artificial Intelligence and Decision Making, 2011 Issue 3, Pages 26–33 (Mi iipr467)

Knowledge engineering

Fuzzy systems identification based on direct ant colony algorithm

I. A. Hodashinsky, P. A. Dudin

Tomsk State University of Control Systems and Radioelectronics

Abstract: In paper, the singleton-type fuzzy system is considered. The direct ant colony algorithm for systems identification is offered. Working capacity of identification algorithm is confirmed by a number of simulating experiments in which course algorithm parameters varied. The comparative analysis of the received results with analogues is given.

Keywords: fuzzy systems identification, ant colony optimization.



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