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 :
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