DocumentCode
3356693
Title
Research on intelligent drainage control strategy of tunnel based on GABP
Author
Chengqian, Ma ; Min, Chen ; Yan, Gao
Author_Institution
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
fYear
2010
fDate
26-28 June 2010
Firstpage
2891
Lastpage
2894
Abstract
In this paper, the author uses the genetic algorithms (GA) to optimize the traditional BP neural network model, and establish the GABP neural network model. The Zhongshan Road underground passage of Wuchang Railway station is taken as the object of study to establish the tunnel drainage system based on the GABP neural network and does the simulation experiment. Compare to the traditional BP neural network, GABP can reduce the computational amount and training time, speed up convergence and improve forecast accuracy. Meanwhile, by adopting the method of combination of quality and quantity to do the system analysis and synthesis, the design of the controller will shake off restricts of system model, make the algorithm simple and the robustness great.
Keywords
backpropagation; control system synthesis; genetic algorithms; intelligent control; neurocontrollers; railways; robust control; GABP neural network; Wuchang Railway station; Zhongshan Road underground passage; controller design; forecast accuracy; genetic algorithms; intelligent drainage control strategy; Algorithm design and analysis; Computational modeling; Computer networks; Control system synthesis; Convergence; Genetic algorithms; Intelligent control; Network synthesis; Neural networks; Rail transportation; BP neural network model; GABP neural network; genetic algorithms; intelligent drainage system;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7737-1
Type
conf
DOI
10.1109/MACE.2010.5536080
Filename
5536080
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