Published 2021-01-01
“…Under the background of global climate change,the frequency of extreme rainfall events increases,and the urban water-logging disaster occurs frequently.The risk assessment of water-logging disaster can effectively reduce the loss.Taking Haojiang District of Shantou City as case study,this paper improves the weights of the analytic hierarchy process (AHP) by neural network,expands the traditional nine-point scaling,and constructs the water-logging disaster risk evaluation model.The results show that the water-logging disaster risk in Haojiang District is generally high in the south-central region and low in the northwest region.Especially,Yuxin Street,Binhai Street,Majiao Street and Dahao Street have higher risk values,which need to take preventive measures.After verification of evaluation results with historical data,it is shown that about 80% of historical flood disaster points are distributed in high-risk areas,which is consistent with the verification results of historical disaster points.The weight determination method of AHP is improved by neural network,the intermediate variables of the traditional nine-point method is expanded to three
decimal places,and the weight is determined by the computer to reduce subjectivity to a certain extent.The results of risk assessment can provide technical support for flood warning and flood control scheduling within a certain time limit.…”
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