A Risk Assessment Method Based on RBF Artificial Neural Network-Cloud Model for Urban Water Disaster
Liu Deng · Yellow River · 2014
Aiming at the uncertainty characteristics of urban water disaster system,this paper proposed a risk assessment method based on RBFANN and cloud model( RBF-C). Selecting four basic evaluation factors of urban water disaster and according to the measured hydrological frequency curve,this paper determined the risk limits corresponding to each level and generated comprehensive cloud models for risk levels of each evaluation factor. Using the evaluation factors of measured time series to establish RBF-ANN,the predictive values were got into the comprehensive cloud model to obtain the distributions of certainty degrees of water disaster risk levels. The study case shows that the RBF-C method can improve the uncertainty problem of the risk ownership in evaluation process and the evaluation results can reflect the risk degree of urban water disaster accurately.