| At present, the design methods of pile axial ultimate bearing capacity for offshore oil jacket platform commonly used include API RP2A (American petroleum institute) and Cone Penetration Test (CPT), based on these two methods, the idea of using BP neural network model to calculate the pile axial ultimate bearing capacity is proposed，which could effectively predict the pile axial ultimate bearing capacity.According to the characteristics of BP neural network algorithm with strong nonlinear mapping ability and learning function, through the analysis of factors affecting the single pile ultimate bearing capacity, the prediction model of axial ultimate bearing capacity based on BP neural network is established based on the CPT data. By using the analysis results of API RP2A method to study, train and test the prediction of the model, it is proved that the prediction model has good performance, high accuracy and fast convergence speed, and the feasibility of the neural network method is verified. The prediction results can guide the pile foundation design and shorten the period. Therefore, it has great practical value in engineering. |
