Document Type


Publication Date



During typhoon periods, accurate hourly rainfall forecasts are extremely important. A new typhoon rainfall forecasting model that integrates multi-objective genetic algorithm (MOGA) with support vector machines (SVM) is presented in this paper. Apart from the rainfall data, the meteorological variables are also considered. An application to high- and low-altitude meteorological stations has shown that the proposed model yields the best performance as compared to other models. Results indicate that meteorological variables are helpful. The proposed model significantly improves hourly typhoon rainfall forecasting, especially for the long lead time forecasting. Moreover, the optimal combination of inputs is determined by the proposed model for each lead time forecasting. The use of the optimal combination of inputs yields more accurate forecasts than the use of all inputs. In conclusion, the proposed model is expected to be useful for effective hourly typhoon rainfall forecasting.


Session R32, Hydrologic Modeling: Forecasting



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.