Regional Disaster Risk Assessment Based on ARIMA Prediction and Comprehensive Evaluation Model - Cui, Chuanhui; Dong, Meiting; Li, Haiqing (Transactions on Computer Science and Intelligent Systems Research, 2024)
The occurrence of extreme weather events affects the natural economic and social security, and has a serious impact on some industries, so the prediction and evaluation of disaster risk level is particularly important. This paper collected data on nine indicators from 25 regions and divided them into four areas: extreme weather, natural, social, and economic. the ARIMA prediction model is used to predict the probability and intensity of extreme weather in the future. The combined weights of each index were calculated by Composite Weighting Method, including principal component analysis, entropy weight method and coefficient of variation method, and the Risk Assessment Index (RAI) formula was constructed, and then the WNSE prediction and evaluation model was constructed. It is divided into four risk levels by fuzzy cluster analysis. We use WNSE prediction and evaluation model to calculate New York City and Switzerland’s RAI and coverage levels. Using this prediction, we can assess the severity of the consequences of natural disasters and prevent or remedy them. The assessment of regional disaster risk levels can give relevant reference to the government, and the government can make reasonable resource allocation.