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| Research on the Stability Prediction of Dangerous Rocks on Railway Slopes Based on Intelligent Algorithms |
| JIN Chunling1, LIU Jingjing1, GONG Li1, CUI Wenxiang1, LAO Zhengchang2 |
1. Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China;
2. Nanning Depot, China Railway Nanning Bureau Group Co. Ltd, Nanning, Guangxi 530000, China |
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Abstract Research purposes: In railway construction and operation and maintenance, dangerous rock is a key problem in the prevention and control of geological hazards on side slopes. In order to achieve accurate and rapid prediction of the stability state of dangerous rocks on railway slopes and improve the accuracy of protection along railway lines, a new method of predicting the stability of dangerous rocks on railway slopes based on PCA improved GASA-FCM model (Genetic Algorithms Simulated Annealing C-Means, GASA-FCM) is proposed. The accuracy and superiority of the model are verified based on the Luoman-Mawei section of the Qiangui line.
Research conclusions: (1) Considering the slope and dangerous rock condition, physical and mechanical properties of rock body and hydrogeological conditions, a railway slope dangerous rock stability prediction index system containing 13 secondary indicators is constructed. (2) Compared with the traditional FCM model and GA-FCM model, the GASA-FCM prediction model proposed in this paper has stable convergence value and smaller mean square error. (3) The model is used in the prediction and evaluation of the stability level of dangerous rocks in the slope of the Luoman-Mawei section, and the results are fully consistent with the actual survey results, which verifies the accuracy and superiority of the model. (4) The research results can provide reference for the prediction and evaluation of the stability level of dangerous rocks along other railway projects, which is of great significance to accelerate the information management of the whole railway line.
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Received: 21 June 2022
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2023, Vol. 40 
