Abstract In order to improve the accuracy and reliability of forecasting deformation rnonitoring data, two kinds of combination prediction model structure, series combination（SC)and parallel combination(PC） are proposed.In the SC time series model, grey model and neural network to predict are separately used and then
the predicting results are combined. In the PC the weight is used to combine different models, and the performance of the linear and nonlinear weight combination forecast are compared. Finally, a practical prediction case in building safety monitoring forecast used to explain the method. According to the experimental results, the proposed SC and PC combined method obviously can improve the prediction accuracy and therefore can be applied to deformation data analysis.
Gao Ning,Gao Caiyun. ON MODEL AND FORECAST OF DEFORMATION MONITORING DATA
BASED ON SERIES AND PARALLEL COMBINATION PREDICTION[J]. jgg, 2013, 33(3): 116-120.
Gao Ning,Gao Caiyun. ON MODEL AND FORECAST OF DEFORMATION MONITORING DATA
BASED ON SERIES AND PARALLEL COMBINATION PREDICTION[J]. jgg, 2013, 33(3): 116-120.
