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为减小水下隧道涌水对人员安全及隧道施工的不利影响,需要对水下隧道涌水进行风险评价和预测。基于文献调查和专家评价方法,结合工程实际,利用层次分析法(AHP)构建水下隧道涌水灾害评价体系,从地质因素、水文条件及隧道工程3个方面提出11个评价指标。采用物元分析法和AHP法,进行合成确定各评价指标权重。以BP神经网络作为评价工具,构建涌水灾害综合评价预测模型。以某水下隧道为例,进行评价和预测分析。结果表明,基于物元分析和AHP的BP神经网络评价模型预测误差不大于3.2%。
In order to reduce the adverse impact of water tunneling on personnel safety and tunnel construction, risk assessment and prediction of underwater tunnel water inflow is needed. Based on the literature survey and expert evaluation method, combined with the engineering practice, this paper constructs the evaluation system of underwater tunnel water inflow disaster using Analytic Hierarchy Process (AHP), and puts forward eleven evaluation indexes from three aspects of geological factors, hydrological conditions and tunnel engineering. The method of matter element analysis and AHP were used to determine the weight of each evaluation index. With BP neural network as the evaluation tool, a forecasting model of water inrush disaster is constructed. Taking an underwater tunnel as an example, the evaluation and prediction analysis are carried out. The results show that the prediction error of BP neural network model based on matter element analysis and AHP is not more than 3.2%.