A new method for predicting the vertical ultimate bearing capacity of statically-pressured pipe pile is established by using artificial neural network based on principal component analysis and conjugate gradient algorithm. The integrated variables are determined through the principal component analysis of factors which influenced the ultimate bearing capacity of single pile. Then

the artificial neural network with integrated variables as input and ultimate bearing capacity as output is confirmed. Also

the conjugate gradient algorithm is applied to computing the weight values and threshold values with given samples in order to obtain the network of predicting ultimate bearing capacity. At last

the engineering examples are used to verify the established model. It could be concluded that it is feasible to predicting the ultimate bearing capacity of statically-pressured pipe pile with this model

which has a better prediction accuracy and applicability. This method provides a new way to analyze the vertical bearing character of statically-pressured pipe pile

and gives references to the relevant problems.