APPLICATION OF BP NEURAL NETWORK BASED ON KALMAN FILTERING TO DAM DEFORMATION PREDICTION
Li Jiebin 1,2) ; and Kong Lingjie 1,2)
1)School of Geological and Surveying Engineering, Chang’an University, Xi’an 7100542)School of Space Positioning Technology and Information Institute, Xi’an 710054
Abstract A new dam deformation perdition model of BP neural network based on Kalman filtering are put forward. The filtered sample data is used for BP training, it makes the network have dynamic properties and reduces the possibility of the local minimum value of Neural network. The precision and generalization ability of BP based on Kalman filtering are higher than those of the traditional BP neural network. Through the example it is proved that the new algorithm is of high accuracy and generalization ability in the data processing.
Key words ：
Kalman filtering
BP neural network
generalization ability
prediction
model error
Received: 01 January 1900
Corresponding Authors:
Li Jiebin
Cite this article:
Li Jiebin,and Kong Lingjie. APPLICATION OF BP NEURAL NETWORK BASED ON KALMAN FILTERING TO DAM DEFORMATION PREDICTION[J]. , 2009, 29(4): 124-126.
Li Jiebin,and Kong Lingjie. APPLICATION OF BP NEURAL NETWORK BASED ON KALMAN FILTERING TO DAM DEFORMATION PREDICTION[J]. jgg, 2009, 29(4): 124-126.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2009/V29/I4/124
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