DocumentCode :
1702981
Title :
Micro-genetic algorithms in the optimisation of neuro-fuzzy controllers
Author :
Jerabek, Vratislav ; Lachiver, Gerard
Author_Institution :
Dept. of Electr. & Comput. Eng., Sherbrooke Univ., Que., Canada
Volume :
1
fYear :
1995
Firstpage :
109
Abstract :
The neuro-fuzzy network is a combination of fuzzy logic and neural nets which benefits from both approaches. A backpropagation algorithm applied to such a network may converge towards a local optimum. The authors apply the micro-genetic algorithm to optimise the architecture of the neuro-fuzzy network and to ensure its convergence towards the global optimum. This algorithm accomplishes crude approximation of the network architecture near a global optimum, towards which its direct convergence is afterwards brought about by backpropagation
Keywords :
backpropagation; control system synthesis; convergence; fuzzy control; genetic algorithms; neural net architecture; neurocontrollers; backpropagation algorithm; convergence; global optimum; local optimum; micro-genetic algorithms; network architecture approximation; neuro-fuzzy controllers; neuro-fuzzy network; optimisation; Convergence; Decoding; Noise measurement; Resumes; Tires;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 1995. Canadian Conference on
Conference_Location :
Montreal, Que.
ISSN :
0840-7789
Print_ISBN :
0-7803-2766-7
Type :
conf
DOI :
10.1109/CCECE.1995.528086
Filename :
528086
Link To Document :
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