Using Unscented Kalman Filter for Training the Minimal Resource Allocation Neural Network

2005 ◽  
pp. 8-14 ◽  
Author(s):  
Ye Zhang ◽  
Yiqiang Wu ◽  
Wenquan Zhang ◽  
Yi Zheng
Keyword(s):  
Neural Network ◽  
Resource Allocation ◽  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Minimal Resource

Prediction Model of Concrete Dam Deformation Based on Adaptive Unscented Kalman Filter and BP Neural Network

2014 ◽  
Vol 513-517 ◽  
pp. 4076-4079 ◽  
Author(s):  
Liang Hui Li ◽  
Sheng Jun Peng ◽  
Zhen Xiang Jiang ◽  
Bo Wen Wei
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Unscented Kalman Filter ◽  
Safety Monitoring ◽  
Hydraulic Engineering ◽  
Concrete Dam ◽  
Adaptive Unscented Kalman Filter ◽  
Dam Deformation

By using unscented kalman filter (UKF) theory and introducing adaptive factor into BP neural network, a new prediction model of concrete dam deformation was proposed. Example shows that this model can improve the convergence speed of BP neural network, and the calculation precision of this model meets engineering requirements. Meanwhile, this model can be applied in the safety monitoring of other hydraulic engineering structure.

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