| Title |
Evolutionary Nonlinear Compensation and Support Vector Machine Based Prediction of Windstorm Advisory |
| DOI |
https://doi.org/10.5370/KIEE.2017.66.12.1799 |
| Keywords |
Windstorm. prediction ; GP nonlinear compensation ; SVM ; AWS ; UM ; KLAPS |
| Abstract |
This paper introduces the prediction methods of windstorm advisory using GP nonlinear compensation and SVM. The existing special report prediction is not specialized for strong wind, such as windstorm, because it is based on the wide range of predicted values for wind speed from low to high. In order to improve the performance of strong wind reporting prediction, a method that can efficiently classify boundaries of strong wind is necessary. First, evolutionary nonlinear regression based compensation technique is applied to obtain more accurate values of prediction for wind speed using UM data. Based on the prediction wind speed, the windstorm advisory is determined. Second, SVM method is applied to classify directly using the data of UM predictors and windstorm advisory. Above two methods are compared to evaluate of the performances for the windstorm data in Jeju Island in South Korea. The data of 2007-2009, 2011 year is used for training, and 2012 year is used for test. |