NDLI: Application of elevator group control system based on genetic algorithm optimize BP fuzzy neural network

Content Provider	IEEE Xplore Digital Library
Author	Yanqiu Wang Jian Zhang Yueling Zhao Yu Wang
Copyright Year	2008
Description	Author affiliation: Liao Ning Univ. of Technol., Jinzhou (Yanqiu Wang; Jian Zhang; Yueling Zhao; Yu Wang)
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.
Starting Page	8702
Ending Page	8705
File Size	292955
Page Count	4
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4594612
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithms Elevators Control systems Gallium Fuzzy control Mathematical model Fuzzy neural networks fuzzy neural network Elevator Group Control System genetic algorithm BP neural network
Content Type	Text
Resource Type	Article

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Application of elevator group control system based on genetic algorithm optimize BP fuzzy neural network