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.
| Original language | English |
|---|---|
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Complexity International |
| Volume | 3 |
| Publication status | Published - 1 Apr 1996 |
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Evolutionary learning in fuzzy logic control systems. / Stonier, Russel; Mohammadian, Masoud.
In: Complexity International, Vol. 3, 01.04.1996, p. 1-17.Research output: Contribution to journal › Article
TY - JOUR
T1 - Evolutionary learning in fuzzy logic control systems
AU - Stonier, Russel
AU - Mohammadian, Masoud
PY - 1996/4/1
Y1 - 1996/4/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=4544334939&partnerID=8YFLogxK
M3 - Article
VL - 3
SP - 1
EP - 17
JO - Complexity International
JF - Complexity International
SN - 1320-0682
ER -