Citation

Li Q, Zhou J, Liu D, Jiang X. Safety Sci. 2012; 50(5): 1275-1283.

Copyright

(Copyright © 2012, Elsevier Publishing)

DOI

10.1016/j.ssci.2012.01.007

PMID

unavailable

Abstract

Floods have become increasingly alarming worldwide. Flood risk management in terms of assessing disaster risk properly is a great challenge that society faces today. Natural disaster risk analysis is typically beset with issues such as imprecision, uncertainty, and partial truth. There are two basic forms of uncertainty related to natural disaster risk assessment, namely, randomness caused by inherent stochastic variability and fuzziness due to macroscopic grad and incomplete knowledge sample. However, the traditional probability statistical method ignores the fuzziness of risk assessment with incomplete data sets and requires a large sample size of data. The fuzzy set methodology is introduced in the area of disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The present paper puts forward a composite method based on variable fuzzy sets and information diffusion method for disaster risk assessment. The results indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management. We hope that by conducting such risk analysis, the impact of flood disasters can be mitigated in the future.