Risk evaluation is an effective way to reduce the impacts of natural hazards\nand it plays an increasingly important role in emergency management. Traditional\nmethods of assessing risks mainly utilize Geographic Information System\n(GIS) to get risk map, and information diffusion method (IDM) to deal\nwith incomplete data sets. However, there are few papers discuss the uncertainty\nof integrated hazards and consider dynamic risk under time dimension.\nThe model proposed in this study combines the variable fuzzy set theory\nwith information diffusion method (VFS-IDM) to solve the uncertainness of\nmultiple hazards dynamic risk assessment when data sets are incomplete.\nThis study employs fuzzy set theory (VFS) to calculate the relative membership\ndegree and applies information entropy method (IEM) to obtain the\nweights of criteria indicators for multiple hazards evaluation. Then applies\ninformation diffusion method (IDM) to estimate condition probability distribution\nand vulnerability curve with the VFS-IEM model results, time data\nand multiple hazards losses. Then the expected value of multiple hazards dynamic\nrisk can be calculated by using the normal information diffusion estimator\nso as to improve the accuracy of risk evaluation results.
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