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순환신경망을 이용한 제주지역 겨울철 저층윈드시어 예측 KCI 등재

Prediction of Low-level Wind Shear for the Winter in the Jeju Area using Recurrent Neural Network

  • 언어KOR
  • URLhttps://db.koreascholar.com/Article/Detail/383149
  • DOIhttps://doi.org/10.14383/cri.2019.14.3.199
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기후연구 (Journal of Climate Research)
건국대학교 기후연구소 (KU Climate Research Institute)
초록

Ensemble verification and prediction of low-level wind shear (LLWS) are an important matter for airplane landing and management. In this study, we compared the prediction performance of LLWS forecasts of ensemble mean, multiple regression model and long short-term memory (LSTM), which belong to the family of recurrent neural network based on the grid points over the Jeju area. The prediction skills of methods were compared by mean absolute error. We found that the prediction skills of forecasts of LSTM were better than the bias-corrected forecasts in terms of deterministic prediction.

목차
Abstract
1. 서론
2. 자료 및 분석 방법
    1) 자료
    2) 분석방법
3. 분석 결과
4. 결론
References
저자
  • 김찬수(공주대학교 응용수학과) | Chansoo Kim (Department of Applied Mathematics, Kongju National University) Correspondence