DocumentCode
3358802
Title
RBF neural network prediction method of deformation monitoring data
Author
Wang, Guo-hui ; Li, Ma ; Chen, Hai-tao
Author_Institution
Fac. of Civil & Transp. Eng., Guangdong Univ. of Technol., Guangzhou, China
fYear
2010
fDate
26-28 June 2010
Firstpage
4874
Lastpage
4876
Abstract
In order to improve the precision and reliability of prediction of deformation monitoring data, radial basis function artificial neural network is used in deformation monitoring data processing. The prediction result of this method is compared with the prediction result of BP neural network prediction methods, and it is concluded that through the radial basis function artificial neural network better prediction result can be obtained.
Keywords
backpropagation; radial basis function networks; BP neural network prediction method; RBF neural network prediction method; deformation monitoring data prediction; deformation monitoring data processing; precision; radial basis function artificial neural network; reliability; Artificial neural networks; Data engineering; Data processing; Monitoring; Neural networks; Prediction methods; Reliability engineering; Transportation; RBF artificial neural network; deformation monitoring; deformation prediction;
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.2010.5536200
Filename
5536200
Link To Document