Risk assessment of urban waterlogging and site selection of storage tank based on MCDM-BPNN
To establish a comprehensive evaluation system for urban waterlogging risk,three dimensions were selected:water accumulation risk,overload risk,and lateral inflow.This system aims to provide a reference for the optimal placement of storage tanks.Firstly,a mixed MCDM framework including the improved analytic hierarchy process(IAHP),anti-entropy weight method(AEW),and technique for order preference by similarity to ideal solution(TOPSIS)was designed.Then,the IAHP-AEW-TOPSIS model was compared with IAHP-TOPSIS and AEW-TOPSIS model respectively,and the ranking consistency was verified by Spearman ranking correlation coefficient.The performance of IAHP-AEW-TOPSIS model was confirmed by calculating variation coefficient,relative range and sensitivity.Finally,a model based on MCDM-BPNN was established and verified by a waterlogging-prone area in Shanxi Province.The results show that water accumulation risk has the most significant influence in the evaluation system of urban waterlogging risk,with the weight of 0.46,followed by the overload risk with the weight of 0.36.The location of the node and the number of connecting pipes greatly affect the risk of waterlogging of the node,and waterlogging occurs more frequently at the junction of pipes or in larger confluence areas.There was better performance exhibited by the IAHP-AEW-TOPSIS model.In the 5-year and 10-year return periods,the accuracy of MCDM-BPNN model verification set is 93.3%and 100%respectively,which can accurately and rapidly simulate and predict urban floods.After the application case is set up,the number of high,medium and low risk nodes are 7,9,30 and 6,19,21 respectively,and the effect of reducing waterlogging overflow is remarkable.
multi-criteria decision making(MCDM)back propagation neural networks(BPNN)urban waterloggingrisk assessmentstorage tank
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