ISSN:
1433-3058
Keywords:
Fuzzy logic
;
Genetic algorithms
;
Knowledge acquisition
;
Learning
;
Neural networks
;
Optimisation
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract This paper presents an automated knowledge acquisition architecture for the truck docking problem. The architecture consists of a neural network block, a fuzzy rule generation block and a genetic optimisation block. The neural network block is used to quickly and adaptively learn from trials the driving knowledge. The fuzzy rule generation block then extracts the driving knowledge to form a knowledge rule base. The driving knowledge rule base is further optimised in the genetic optimisation block using a genetic algorithm. Computer simulations are presented to show the effectiveness of the architecture.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01413867
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