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www.nonlin-processes-geophys.net/13/443/2006/
doi:10.5194/npg-13-443-2006
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Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study
Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
Abstract. In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is the best model for 3- and 6-h lead time prediction and the only reliable one for 9-h lead time forecasting for the largest flood used as a test case.
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Citation: Piotrowski, A., Napiórkowski, J. J., and Rowiński, P.M.: Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study, Nonlin. Processes Geophys., 13, 443-448, doi:10.5194/npg-13-443-2006, 2006. Bibtex EndNote Reference Manager XML
