Abstract：Partial least-squares regression method can resolve the problem of serious multicollinearity among variables，and the neural network can overcome the shortcoming that the conventional models must be the combination of linearity and non-linearity of imput data. The two methods, neural network model with partial least-squares regression of observation data of dam are combined. The result of an example shows that the prediction is of high precision with the proposed method.
邓念武 邱福清 . 偏最小二乘回归神经网络模型在大坝观测资料分析中的应用[J]. 岩石力学与工程学报, 2002, 21(07): 1045-1048.
Deng Nianwu， Qiu Fuqing. APPLICATION OF NEURAL NETWORK MODEL WITH PARTIAL LEAST-SQUARES REGRESSION INTO INTERPRETATION ON OBSERVATION DATA OF DAM. , 2002, 21(07): 1045-1048.
2002, Vol. 21 
