DocumentCode
534369
Title
Foundation settlement forecasting using the new BP-Gompertz model
Author
Liang, Haonan ; Qin, Feihu ; Wang, Jiehao ; Zhang, Tian ; Liang, Yan
Author_Institution
Sch. of Mech. & Civil Eng., China Univ. of Min. & Technol., Xuzhou, China
Volume
1
fYear
2010
fDate
18-19 Oct. 2010
Abstract
In view of each advantages of Gompertz and BP neural network, the Gompertz growth curve model was combined with BP neural network. The BP-Gompertz foundation forecasting model was proposed through using the capability of approximating the true value of BP neural network to optimize the curve fitting capability of Gompertz. An example shows that compared with the traditional Gompertz model, the prediction accuracy of the new BP-Gompertz model is significantly improved. The model provides a new method for the foundation settlement prediction.
Keywords
approximation theory; backpropagation; curve fitting; foundations; neural nets; optimisation; structural engineering computing; BP neural network; BP-Gompertz Model; Gompertz growth curve model; curve fitting capability; foundation settlement forecasting; prediction accuracy; Computer languages; Measurement uncertainty; Time measurement; BP neural network; BP-Gompertz model; Gompertz growth curve model; foundation settlement;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-8104-0
Electronic_ISBN
978-1-4244-8106-4
Type
conf
DOI
10.1109/ICINA.2010.5636420
Filename
5636420
Link To Document