利用人工神经网络强大的非线性映射能力和学习训练功能，提出了基于BP网络的基桩完整性检测模型。
Based on the powerful nonlinear reflection and training function of artificial neural networks, the model of BP neural network for foundation piles integrity testing is put forward.
本文的工作证明人工神经网络可以模拟桩的贯入特性，所作的计算具有工程实用性。
It is verified that artificial neural network can simulate the penetrating characteristics of pile and the calculation achieved is useful in engineering.
利用ANFIS较强的学习能力和模糊逻辑推理功能，建立了单桩竖向极限承载力预测的自适应网络模糊推理系统。
Based on the strong learning ability and fuzzy logic function of ANFIS, a method for predicting vertical ultimate bearing capacity of single pile is presented.
应用推荐