Pre-stressed precast high strength concrete (PHC) nodular piles with hyper-MEGA construction method are favorably used in medium to high-rise building foundations. In this study, a feed-forward neural network (FFNN) was adopted to investigate the ultimate axial load bearing capacity of the PHC nodular pile. The network receives the composite pile and geotechnical conditions with eight input neurons and outputs the nodular pile's ultimate axial load bearing capacity. Among numerous possible FFNN network architectures, the most accurate one is determined by optimizing the hidden layer. Network training is conducted with Bayesian regularization backpropagation (BRB); the training datasets consist of static pile load test and standard penetration test index of soil profile collected from various projects in Vietnam. The significance of each input parameter is quantified with importance-based sensitivity analysis. An explicit function has been constructed from weights and bias values at each neuron in the FFNN to estimate the axial load bearing capacity. The excellent agreement of all output values by the proposed FFNN with the measured values proved the model’s robustness and reliability. The predictive capacity of the proposed FFNN model has significantly outperformed all current empirical formulas. The outcome of this study can be directly put into engineering practice to furnish an economically optimal design of the composite nodular pile.

采用超MEGA施工方法的预应力预制高强混凝土（PHC）球桩桩在中高层建筑地基中具有良好的应用前景。在这项研究中，采用前馈神经网络（FFNN）来研究 PHC 球状桩的极限轴向承载能力。该网络通过八个输入神经元接收复合桩和岩土条件，并输出结节桩的极限轴向承载能力。在众多可能的 FFNN 网络架构中，最准确的一种是通过优化隐藏层来确定的。使用贝叶斯正则化反向传播（BRB）进行网络训练；训练数据集包括静态桩载测试和从越南各个项目收集的土壤剖面标准渗透测试指数。每个输入参数的重要性通过基于重要性的敏感性分析来量化。已根据 FFNN 中每个神经元的权重和偏差值构建了一个显式函数，以估计轴向承载能力。所提出的 FFNN 的所有输出值与测量值的出色一致性证明了该模型的鲁棒性和可靠性。所提出的 FFNN 模型的预测能力明显优于所有当前的经验公式。本研究成果可直接应用于工程实践，为复合材料球桩提供经济优化设计。所提出的 FFNN 的所有输出值与测量值的出色一致性证明了该模型的鲁棒性和可靠性。所提出的 FFNN 模型的预测能力明显优于所有当前的经验公式。本研究成果可直接应用于工程实践，为复合材料球桩提供经济优化设计。所提出的 FFNN 的所有输出值与测量值的出色一致性证明了该模型的鲁棒性和可靠性。所提出的 FFNN 模型的预测能力明显优于所有当前的经验公式。本研究成果可直接应用于工程实践，为复合材料球桩提供经济优化设计。