Error Forecasting Using Linear Regression Model
* 본 문서는 배포용으로 복사 및 편집이 불가합니다.
서지정보
ㆍ발행기관 : 한국습지학회
ㆍ수록지정보 : 한국습지학회지 / 13권 / 1호
ㆍ저자명 : Lian Guey Ler, Byung Sik Kim, Gye Woon Choi, Byung Hwa Kang, Jung Jae Kwang
ㆍ저자명 : Lian Guey Ler, Byung Sik Kim, Gye Woon Choi, Byung Hwa Kang, Jung Jae Kwang
목차
Abstract1. Introduction
2. Model Description
3. Data Assimilation
4. Methodology
5. Case Study
6. Conclusion
Acknowledgements
References
한국어 초록
In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.영어 초록
In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.참고 자료
없음"한국습지학회지"의 다른 논문
- 수리조건을 이용한 생물서식처 적합도 지수 산정12페이지
- 왕귀뚜라미(Teleogryllus emma)감각 정보 제공에 따른 긴호랑거미(Argiope brue..10페이지
- 질산화 활성슬러지 내에서의 클린다마이신 항생제 생분해9페이지
- 하수 처리시설의 공간 및 운전인자에 따른 항생제 내성의 통계학적 분석11페이지
- 레이더 자료의 해상도를 고려한 분포형 강우-유출 모형의 GIS 자료 최적 격자의 결정12페이지
- 황새서식처 복원지역에서의 소택지 조성 적지선정 연구10페이지
- 충적하천에서 수제에 의한 안정하도 확보기술에 관한 연구16페이지
- 도심하천과 자연하천의 식생형에 따른 조류 서식지 유형분석11페이지
- Bootstrap 방법 및 SIR 알고리즘을 이용한 예상홍수피해액의 불확실성 분석14페이지
- Hydro-hypsographic 분석을 이용한 근소만 해수 교환 특성 연구8페이지