Identification of Safety Risk Factors for Shield Construction in Urban Drainage Deep Tunnel Based on Text Mining

Shield construction of deep tunnels for urban drainage involves many risk factors, and potential safety hazards are difficult to monitor and identify directly. In order to improve the risk management level of shield construction in urban drainage deep tunnel, this study proposes a method for identifying risk factors by combining text mining technology and the entropy weight method. By using this method, 34 safety risk factors were successfully extracted from the safety accident reports of urban drainage deep tunnel shield construction and the related text data. The results of this study show that the text mining method could play an important role in the risk management of urban drainage deep tunnel shield construction; the introduction of the entropy weight method further improved the accuracy of risk factor identification. The results of this study not only enrich the research content of risk management in urban drainage deep tunnel shield construction but also provide theoretical guidance for managers to formulate risk management measures and optimize risk management procedures.