根据钻孔桩和打击桩的原型试验观测的数据,运用人工智能方法对横向承载桩和轴向承载桩 的工作特性进行模拟,并利用标准贯入试验(SPTN)值和桩的几何特性等简单的输入数据,开 发出相应的优化神经网络模型;然后,运用反向传播神经网络模型和广义回归神经网络模型分 别对某工程的钢筋混凝土桩进行分析,并将求得的预测结果与常规设计法的结果进行比较, 结果表明神经网络方法比传统方法有明显的优越性,在实际工程设计中具有重要的参考价值 和现实意义。

Artifical intelligence methods are implemented to simulate the behaviors of axially and laterally loaded piles using the field observation tests data obtain ed f rom the drilled shafts and driven piles.The optimal neural network model is deve loped using only simple input data of SPTN values and piles' geometrical featu r es etc..The analysis for R.C piles of some projects is performed adopting the BP N N and GRNN models respectively,and the obtained predicated results are compared w ith the data from conventional design method.It demonstrated the obvious advanta ges of neural networks in the design of pile foundations over the traditional me thods.This paper has an important practical significance and a referential worth iness in the design of pile foundations.