Abstract

In this article, a novel artificial intelligence method, i.e. random forest (RF), was adopted as a computer-aided tool to predict the vertical displacement of several pile-supported bridge piers above two overlapped earth-pressure-balanced machine (EPBM) tunnels. Naive Bayes theory was introduced for the statistical analysis of the results predicted by the RF method to address the operational variables of the EPBMs required to safely pass beneath the bridge piers. The in situ observations indicated that the EPBM variables were reasonably determined based on the fact that the vertical displacements of the concerned piers were successfully controlled within the allowable range.

摘要

本文采用一种新颖的人工智能方法，即随机森林（RF）作为计算机辅助工具，对两条重叠土压平衡机（EPBM）隧道上方的几个桩支撑桥墩的垂直位移进行预测。 . 朴素贝叶斯理论被引入对 RF 方法预测的结果进行统计分析，以解决安全通过桥墩下方所需的 EPBM 的操作变量。现场观测表明，EPBM变量的确定是基于有关桥墩的竖向位移成功控制在允许范围内的事实。