Abstract：To improve the state prediction of thousand-meter scale cable-stayed bridge by indeterminate factors such as measurement noise and initial component error during the construction process, a state prediction method based on the evidence theory and grey-neural network model is proposed. The fusion theory makes it possible to effectively predict even in the case of insufficient samples or incomplete data. The validity and accuracy of the proposed method is demonstrated through actual structure. Compare and analyze the result of traditional method and the proposed. Practice results show that the parameter prediction based on the evidence theory and grey-neural network model can improve the estimation accuracy of traditional method.
孟庆成;齐 欣;李 乔;卜一之. 证据理论结合灰色神经网络混合识别方法在苏通长江大桥状态预测中的应用[J]. , 2009, 28(11): 96-99.
MENG Qingcheng;QI Xin;LI Qiao;Bu Yizhi. The research of state prediction based on the evidence theory and grey-neural network model for SU-TONG Bridge . , 2009, 28(11): 96-99.
2009, Vol. 28 
