DocumentCode :
2558665
Title :
Application of improved BP neural network in predicting subsidence of buildings
Author :
Fu, Bo ; Xie, Zhenhong
Author_Institution :
Sch. of Surveying & Prospecting Eng., Jilin Inst. of Archit. & Civil Eng., Changchun, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
389
Lastpage :
392
Abstract :
With the increase of engineering construction, the safety of engineering became a realistic problem of great importance. As a major technical means, prediction of deformation monitoring was extremely important for construction and operation of buildings. In this paper, an improved BP neural network was adopted and a nonlinear coefficient was added in the response function of the neurons to enhance the approximation performance of the network. The cumulative subsidence of the 40th to the 43rd interval was predicted and compared with the measured data through training the subsidence monitoring data of total 35 intervals of 14 monitoring points of presupposition around Changchun Science & Technology Museum as sample data. The 1-5-4 network model based on improved BP network reached error demands by 4428 times training. The result showed that the prediction errors of 11 monitoring points were less than 0.5mm and the model performed well.
Keywords :
backpropagation; building; condition monitoring; construction; deformation; neural nets; safety; structural engineering computing; Changchun Science & Technology Museum; building subsidence prediction; buildings construction; buildings operation; deformation monitoring; engineering construction; engineering safety; error demands; improved BP neural network-based 1-5-4 network model; monitoring points; network approximation performance; neurons response function; nonlinear coefficient; prediction errors; subsidence monitoring data; Artificial neural networks; Biological neural networks; Buildings; Mathematical model; Monitoring; Neurons; Predictive models; Back-Propagation neural network; nonlinear coefficient; prediction; subsidence monitoring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234641
Filename :
6234641
Link To Document :
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