| Year of Publication | 2015 | Division | 수치자료응용과(종) |
|---|---|---|---|
| Title | AWS 지점별 기상데이터를 이용한 진화적 회귀분석 기반의 단기 풍속 예보 보정기법 | ||
| Author | 현병용 | ||
| Coauthor | 서기성, 이용희 | ||
| ISBN(ISSN) | 2287-4364 | Name of Journal | 전기학회논문지 |
| Category (International/Domestic) | 국내 | Vol. No. | 64 |
| Research Project Title | 예보기술 지원 및 활용연구 (2015년) | Publication Date | 2015-01-02 |
| Keywords | Wind speed prediction, MOS(Model Output Statistics), Genetic programming, AWS(Automatic Weather Station) | ||
This paper introduces an evolutionary nonlinear regression based compensation technique for the short-range prediction of wind speed using AWS(Automatic Weather Station) data. Development of an efficient MOS(Model Output Statistics) is necessary to correct systematic errors of the model, but a linear regression based MOS is hard to manage an irregular nature of weather prediction. In order to solve the problem, a nonlinear and symbolic regression method using GP(Genetic Programming) is suggested for a development of MOS wind forecast guidance. Also FCM(Fuzzy C-Means) clustering is adopted to mitigate bias of wind speed data. The purpose of this study is to evaluate the accuracy of the estimation by a GP based nonlinear MOS for 3 days prediction of wind speed in South Korean regions. This method is then compared to the UM model and has shown superior results. Data for 2007-2009, 2011 is used for training, and 2012 is used for testing
