Flood Risk Assessment Based on the Information Diffusion Method

This paper presents a composite method for flood disaster risk assessment using a BP artificial neural network and information diffusion technique. Due to the fact that the traditional mathematical statistical model can hardly analyze flood risk issues when the sample size is small, information diffusion theory is suggested to extract as much useful information as possible from the sample and thus improves the accuracy of system recognition. Meanwhile, an artificial neural network model-BP neural network is used to map multi-dimensional space of disaster situation to one-dimensional disaster situation and to raise the grade resolution of flood disaster loss. Furthermore, its application is verified in the flood risk analysis in Henan Province, China, and the risks of different flood grades are obtained. The results indicate that the methods are effective and practical and therefore the model is considered to have a good application prospect in disaster risk assessment.