基于神经网络的蓄滞洪区洪灾风险模糊综合评价

Fuzzy Risk Assessment of Flood Hazard Based on Artificial Neural Network for Detention Basin

洪灾风险评价属于多准则、多层次的模糊综合评价问题,在深入分析洪灾风险成因的基础上,以致灾因子、孕灾环境、承灾体属性为准则层,构建了蓄滞洪区洪灾风险评价指标体系,制定了洪灾风险等级和评价标准。基于BP神经网络,构建了蓄滞洪区洪灾风险评价的BP模型,将其应用到50年一遇洪水情况下,大黄铺洼Ⅰ、Ⅱ、Ⅲ区的洪灾风险评价中,结果表明,Ⅰ区洪水危险性高,但人口稀少、经济不发达,洪灾风险程度最低;Ⅲ区洪灾风险程度稍高于Ⅰ区,Ⅱ区洪灾风险程度较高。以上结论与实际情况基本一致,验证了BP评价模型的合理性。

Risk assessment of flood hazard is a problem of multi-principle fuzzy synthetical evaluation. In this paper, based on an analysis of flood hazard factors, a multi-princlple index system was suggested, taking disaster-inducing factors, disaster environment gestations, properties of hazard bearing body as principle indices. Evaluation grade and standard of flood hazard were established. A method of assessing flood hazards in detention basin was formulated, based on BP neural networks. Then it was applied to the risk evaluation in Dahuangpuwa in Haihe River basin, with the flood-control standard of once in fifty years. The results show that flood hazard risk in Subarea I is low, and it is high in Subarea Ⅱ. The above-mentioned conclutions are accordant with the actual situation, thus verifying the rationality of this method.