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Flood risk assessment is of very importance for disaster mitigation, which is complemented by environment stability, hazard statistical and vulnerability possibility. Each factor usually contains a series of indicators and a comprehensive analysis of each factor must be superimposed on the various indicators. The traditional methods on how to determine the relative weight of each indicator are experts_scoring and AHP, which require a given weight by experts. In this paper, maximum entropy is applied into determining weight of each indicator and cloud model, one kind of uncertain artificial intelligence models, is used to classify the grades of flood risk objectively. Finally, a case study in Huaihe River Basin of China is made and some conclusions are drawn.
Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on (Volume:2 )
Date of Conference: 17-18 July 2010