针对传统经验学习算法(EBL)存在过早收敛的缺陷,引入阴阳对思想进行改进,提出一种基于阴阳对思想的经验学习算法(IEBL)。依托广州市轨道某先隧后站地铁车站工程,基于先行施工的某一断面沉降监测数据,采用基于改进经验学习算法的岩土参数反演方法,获取先隧后站工程的动态岩土参数,并将反演参数应用于先隧后站三维模型数值计算及沉降分析中。结果表明:反演获得的先隧后站工程岩土参数存在空间变异性,随着开挖施工的不断进行,岩土参数产生相应的变化;按照既有设计及施工方法进行先隧后站地铁车站的施工,受横通道及施工顺序等多因素影响,地表最大沉降值出现在地铁车站中部位置,为-5.52 mm;在靠近3#横通道位置存在一定区域的隆起情况,最大隆起为2.26 mm;完整的施工过程引起的地表竖向变形较为稳定,先隧后站施工未对上方道路产生不良影响。

Aiming at the defect of premature convergence of traditional experiential learning algorithm (EBL), Yin-Yang thought is introduced to improve the idea, and an experiential learning algorithm (IEBL) based on Yin-Yang thought is proposed. Based on the settlement monitoring data of a certain section of a subway tunnel before the station project in Guangzhou, the geotechnical parameter inversion method based on improved empirical learning algorithm is adopted to obtain the dynamic geotechnical parameters of the project, and the inversion parameters are applied to the numerical calculation and settlement analysis of the three-dimensional model of the tunnel before the station. The results show that there is spatial variability in the geotechnical parameters obtained by inversion, and the geotechnical parameters change correspondingly with the continuous excavation. The three-dimensional numerical simulation results show that the maximum surface settlement value is -5.52 mm in the middle of the subway station under the influence of multiple factors such as cross passage and construction sequence when the subway station is constructed according to existing design and construction methods. There is a certain area of uplift near the 3# transverse channel, and the maximum uplift is 2.26 mm. The vertical deformation of the ground surface caused by the complete construction process is relatively stable, and the construction of the tunnel before the station has no adverse effect on the road above.