桩基极限承载力与沉降量的神经网络预测

利用BP神经网络较强的高次非一性映射能力和学习功能，建立了基于人工神经网络的单桩极限承载力与沉降量的预测模型。该模型依据现场实测资料建模，避免了计算过程中各种人为因素的影响。通过静载荷试验成果的学习与预测检验，证明其预测精度良好、适用性强，具有较大的工程实用价值。

The Neural Network Prediction Model for the Ultimate Bearing Capacity and Settlement of Piles

By use of the stronger nonlinear mapping and learning a bility of the back propagation neural network , a new model based on this neural network to predict the ultimate bearing capacity and settlement of a single pil e has been presented in this paper, since the model is directly based on in-situ test data, it can avoid the errors due to the artificial factor . By learning and Predicting test of the experimental results of the static local it has prov ed a good predicting accuracy , so it could be used widely in practical engineer ing.