Abstract:This paper explores different prediction models in bridge deformation prediction and attempts to improve their accuracy. Combining bridge deformation monitoring data and the combination forecasting method, a combined forecasting model of the MC error correction and optimization of the bridge is constructed. Through examples, it is concluded that the combination prediction, as compared with single prediction, has higher predictive accuracy and stability, the highest of the RBF neural network combination.Furthermore, optimizing the error correction model further reduces the prediction error; the relative error of prediction results after optimization of the expected value is 0.86% and the variance value is 0.097 3 mm2. The accurate prediction of the deformation of the bridge verifies the effectiveness of this method.