APPLICATION OF THE OPTIMAL NON-NEGATIVE VARIABLE WEIGHT
COMBINATION MODEL FOR MONITORING DAM DEFORMATION
1）College of Geomatics and Geoinformation，Guilin University of Technology,Guilin 541004
2）Guangxi Key Laboratory of Spatial Information and Geomatics，Guilin 541004
Abstract Dam deformation is nonlinear，nonstationary and random which makes it difficult to accurately predict the deformation.Based on three kinds of single model，gray GM（1，1)，BP neural network and the common Carl filtering，the optimal nonnegative variable weight combination forecasting model was proposed.The model inherited the advantages of each single model.It is optimal for local prediction and accuracy is higher for the global prediction.The calculation results were compared with the optimal weighted combination model and each single one.The results show that the model prediction accuracy is higher；the root mean square error is 0.11 mm.And it can be applied to dam deformation prediction practically.
Ren Chao,Liang Yueji,Pang Guangfeng et al. APPLICATION OF THE OPTIMAL NON-NEGATIVE VARIABLE WEIGHT
COMBINATION MODEL FOR MONITORING DAM DEFORMATION[J]. jgg, 2014, 34(6): 162-166.
Ren Chao,Liang Yueji,Pang Guangfeng et al. APPLICATION OF THE OPTIMAL NON-NEGATIVE VARIABLE WEIGHT
COMBINATION MODEL FOR MONITORING DAM DEFORMATION[J]. jgg, 2014, 34(6): 162-166.
