APPLICATION OF BP NEURAL NETWORK BASED ON PRINCIPAL COMPONENT ANALYSIS IN DEFORMATION FORECASTING
Chen Xingquan 1) ; Wang Jiexian 1, 2) ; and Gu Chuan 1)
1)Department of Surveying and Geo-Informatics,Tongji University, Shanghai 2000922)Key Laboratory of Modern Engineering Surveying of SBSM, Shanghai 200092
Abstract In order to improve deformation forecasting precision, application of principal component analysis and improved BP neural network in deformation monitoring is proposed. For the verification if the new method can enhance the precision and reliability of forecasted data, the proposed algorithm is programmed and verified by use of measured data. The results show that compared with other methods, the improved BP neural network based on principal component analysis can achieve better foresting results.
Chen Xingquan ,Wang Jiexian,and Gu Chuan . APPLICATION OF BP NEURAL NETWORK BASED ON PRINCIPAL COMPONENT ANALYSIS IN DEFORMATION FORECASTING[J]. , 2008, 28(3): 72-76.
Chen Xingquan ,Wang Jiexian,and Gu Chuan . APPLICATION OF BP NEURAL NETWORK BASED ON PRINCIPAL COMPONENT ANALYSIS IN DEFORMATION FORECASTING[J]. jgg, 2008, 28(3): 72-76.