Journal
JOURNAL OF HYDROLOGY
Volume 495, Issue -, Pages 52-63Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhydrol.2013.04.050
Keywords
Typhoon rainfall forecasting; Support vector machine; Multi-objective genetic algorithm; Meteorological parameters
Funding
- National Science Council, Taiwan [NSC 101-2625-M-002-007, NSC 99-2221-E-002-092-MY3]
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In this paper, we proposed a new typhoon rainfall forecasting model to improve hourly typhoon rainfall forecasting. The proposed model integrates multi-objective genetic algorithm with support vector machines. In addition to the rainfall data, the meteorological parameters are also considered. For each lead time forecasting, the proposed model can subjectively determine the optimal combination of input variables including rainfall and meteorological parameters. For 1- to 6-h ahead forecasts, an application to high- and low-altitude metrological stations has shown that the proposed model yields the best performance as compared to other models. It is found that meteorological parameters are useful. However, the use of the optimal combination of input variables determined by the proposed model yields more accurate forecasts than the use of all input variables. The proposed model can significantly improve hourly typhoon rainfall forecasting, especially for the long lead time forecasting. (C) 2013 Elsevier B.V. All rights reserved.
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