Evolutionary Learning in Fuzzy Logic Control Systems

Evolutionary Learning in Fuzzy Logic Control Systems Russel Stonier & Masoud Mohammadian
Abstract
	In this paper we discuss the topic of intelligent control by using genetic algorithms to learn fuzzy rules in fuzzy logic control systems. In particular, application is made through simulation studies to collision-avoidance problems and target-tracking for mobile robots. Application to the control of traffic flow approaching a set of intersections and interest rate prediction is also briefly discussed.

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