Flood vulnerability assessment using the triangular fuzzy number-based analytic hierarchy process and support vector machine model for the Belt and Road region

Flood is one of the most serious natural disasters in world. losses developing countries throughout Belt and Road region are more than twice global average. However, to date, extent vulnerability remains poorly understood. Therefore, this study sought address knowledge gap. In study, we presented a assessment model based on triangular fuzzy number-based analytic hierarchy process (TFN-AHP) support vector machine (SVM) model. Firstly, geospatial database including 11 flood conditioning factors was built. Secondly, exposure disaster reduction capability were calculated TFN-AHP SVM, respectively. Finally, spatial distribution generated. According results, areas extremely low, accounting for 86.45% 80.53%, Meanwhile, 47,105,300 km2 low or 93% region. The high-vulnerable (accounting 3.54%) primarily concentrated southern eastern parts China, northern India, Bangladesh, Indus Valley Pakistan, Nile River Basin Egypt, central Indonesia. Obviously, these regions with high characterized by frequent economic activities dense populations. As suggested provides scientific technological evidence prevention mitigation along