DocumentCode :
3019208
Title :
Displacement back analysis on supporting structure of deep foundation pit based on evolutionary neural nrtwork
Author :
Zhao, Sheng-Li ; Liu, Yan
Author_Institution :
Rural & Urban Constr. Coll., Hebei Agric. Univ., Baoding, China
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
171
Lastpage :
174
Abstract :
An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.
Keywords :
backpropagation; foundations; genetic algorithms; geotechnical engineering; neural nets; structural engineering computing; supports; BP network; deep foundation pit; displacement back analysis; evolutionary neural network; genetic algorithm; optimal mechanical parameter; optimization; supporting structure; Algorithm design and analysis; Educational institutions; Electronic mail; Finite element methods; Genetic algorithms; Neural networks; Optimization methods; Pattern analysis; Pattern recognition; Wavelet analysis; BP network; Displacement back analysis; Genetic algorithm; Supporting structure of deep foundation pit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3728-3
Electronic_ISBN :
978-1-4244-3729-0
Type :
conf
DOI :
10.1109/ICWAPR.2009.5207405
Filename :
5207405
Link To Document :
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