中文摘要：

以中国广州新建隧道下穿既有地铁2号线工程为背景,研究对运营地铁隧道实施自动变形监测中智能变形预测的方法.针对地铁监测数据量大、变形分析困难、预测准确率低的技术难题,提出一种基于PBIL支持向量机的地铁智能变形预测模型.通过用基于概率分析的PBIL算法,实现对支持向量机的关键参数组合的精确优化设定,提高了模型的变形预测能力.通过广州地铁穿越工程变形监控工程的应用,该预测方法显示了较高的预测能力和实用性,有效地解决了在条件复杂、环境干扰的地铁运营中较难准确全面监测预警的问题.

英文摘要：

During the construction of crossing engineering, one of the important measures to ensure the safety of subway operation is the implementation of deformation surveying to the existing subway tunnel. Guangzhou new subway line 2 engineering which crosses the existing tunnel is taken as the background. How to achieve intelligent and automatic deformation surveying forecast during the subway tunnel construction process is studied. Because large amount of surveying data exists in the subway construction, deformation analysis is difficult and prediction has low accuracy, a subway intelligent deformation prediction model based on the PBIL and support vector machine is proposed. The PBIL algorithm is used to optimize the exact key parameters combination of support vector machine through probability analysis and thereby the predictive ability of the model deformation is greatly improved. Through applications on the Guangzhou subway across deformation surveying deformation engineering, the prediction method＇s predictive ability has high accuracy and the method has high practicality. It can support effective solution to the implementation of the comprehensive and accurate surveying and early warning under subway operation conditions with the environmental interference and complex deformation.