Research on Identification of Factors Influencing the Cost of Municipal Tunnel Engineering and Risk Control
周宏斌 ZHOU Hong-bin
（广东省建筑设计研究院有限公司，广州 510000）
（Guangdong Provincial Architectural Design and Research Institute Co.，Ltd.，Guangzhou 510000，China）
摘要：本文深入探讨了市政隧道工程造价的影响因素识别与风险控制方法，旨在提高隧道工程建设的经济效益和安全性。在研究过程中，创新性地结合了 BP（Back Propagation）神经网络和模糊均值聚类融合算法，构建了一种精准有效的隧道工程造价建模与估算体系，为隧道工程的投资决策提供了有力的支持。在此基础上，进一步引入了未确知测度理论，结合层次分析法和熵权法，对各项评价指标的权重进行了科学确定。利用未确知测度理论的隧道施工风险评价模型，我们将复杂的施工风险指标进行了量化处理，从而实现了对隧道施工风险的定量评估。这一评估结果不仅有助于准确识别隧道施工中存在的风险点，还为制定针对性的改进措施和施工建议提供了依据。
Abstract: This article explores in depth the identification of influencing factors and risk control methods for the cost of municipal tunnel engineering, aiming to improve the economic benefits and safety of tunnel construction. In the research process, an innovative combination of BP (Back Propagation) neural network and fuzzy mean clustering fusion algorithm was used to construct a precise and effective tunnel engineering cost modeling and estimation system, providing strong support for investment decision -making in tunnel engineering. On this basis, the theory of uncertain measures was further introduced, and the weights of various evaluation indicators were scientifically determined by combining the Analytic Hierarchy Process and Entropy Weight Method. By utilizing the unascertained measurement theory in the tunnel construction risk assessment model, we have quantified complex construction risk indicators, thereby achieving a quantitative evaluation of tunnel construction risks. This evaluation result not only helps to accurately identify the risk points in tunnel construction, but also provides a basis for developing targeted improvement measures and construction suggestions.
关键词：市政工程；工程造价；风险控制；BP 神经网络
Key words: municipal engineering；engineering cost；risk control；BP neural network
中图分类号：TU723.3 文献标识码：A 文章编号：1006-4311（2024）28-007-03 doi:10.3969/j.issn.1006-4311.2024.28.003
|
