An improved attribute recognition method is reviewed and discussed to evaluate the risk of water inrush in karst tunnels. Due to the complex geology and hydrogeology, the methodology discusses the uncertainties related to the evaluation index and attribute measure. The uncertainties can be described by probability distributions. The values of evaluation index and attribute measure were employed through random numbers generated by Monte Carlo simulations and an attribute measure belt was chosen instead of the linearity attribute measure function. Considering the uncertainties of evaluation index and attribute measure, the probability distributions of four risk grades are calculated using random numbers generated by Monte Carlo simulation. According to the probability distribution, the risk level can be analyzed under different confidence coefficients. The method improvement is more accurate and feasible compared with the results derived from the attribute recognition model. Finally, the improved attribute recognition method was applied and verified in Longmenshan tunnel in China.
The remote monitoring and early warning system for subway construction is a Brower/Server (B/S) mode application system which is developed based on web page. The system is applied to tracking, monitoring, reporting, early warning and management in whole areas during subway construction, and the emergency or safety risk site can be warned and treated in advance. The system provides lots of facilities such as the spatial information of building, road, construction plant, the conformation of geology and pipelines, and provides available facilities of storage, display, query, statistics and analysis. The system can manage real-time monitoring and early warning, which has been successfully applied in subway construction in Beijing, Nanjing, Nanchang, etc.
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