STM Article Repository

With the rapid development of high-speed railways in China, it is inevitable that some of the lines will have to traverse through the mine goaf ground, and there is little research on whether the “activation” of the foundation of the mine goaf ground occurs under the influence of train loads. In order to provide a safe and reliable basis for the construction of high-speed railway in mine goaf ground, a new classification method of mine goaf ground activation is proposed considering the stability and railway influence. First, the stability evaluation system of the mine goaf site is established with 3 primary indexes and 12 secondary indexes. The 47 groups’ data of the mine goaf ground site are collected as learning samples. Five machine learning methods including decision tree, discriminant analysis, support vector machine, and classifier ensemble are used to learn and test the data. The optimal algorithm is selected and the stability evaluation model is established to classify the stability of the mine goaf site. Second, influencing factors of railway are graded to establish an extension comprehensive evaluation model. Finally, based on the above two models, a new classification method of high-speed railway goaf ground activation considering the two factors and five sub-factors is proposed. Through the verification of two engineering examples, the prediction result of this method is “easily activation” and the need to treat the goaf area, and the actual construction is also taken to grouting treatment, proving that the method has certain guiding significance for the project.