DocumentCode :
2506532
Title :
Application of elevator group control system based on genetic algorithm optimize BP fuzzy neural network
Author :
Wang, Yanqiu ; Zhang, Jian ; Zhao, Yueling ; Wang, Yu
Author_Institution :
Liao Ning Univ. of Technol., Jinzhou
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
8702
Lastpage :
8705
Abstract :
Its deficiency was revealed because of traffic pattern identification method of elevator group control system based on using BP neural network, and a new traffic patten identification model is proposed which is based on optimizing fuzzy neural network by genetic algorithm. The genetic algorithm is used to train fuzzy BP neural network, which can overcome the shortcoming of local minimum appeared while training the network, and the veracity of the whole traffic pattern identification model can be increased. At last, the sampled data are trained and tested Matlab software, and the simulation results indicate that the proposed identify model has very small error.
Keywords :
backpropagation; fuzzy control; fuzzy neural nets; genetic algorithms; lifts; neurocontrollers; BP fuzzy neural network; elevator group control system; genetic algorithm; optimization; traffic pattern identification; Communication system traffic control; Control system synthesis; Control systems; Elevators; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Mathematical model; Neural networks; Traffic control; BP neural network; Elevator Group Control System; fuzzy neural network; genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594612
Filename :
4594612
Link To Document :
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