논문
Corrigendum to: Random Forest Model for Salinity Prediction in the Nakdong River Estuary Reflecting Spatio-temporal Lag Effects
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주제분류해양공학
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There was an error in the funding statement. The corrected funding information is provided follow. This correction does not affect the scientific conclusions of the article. Corrected Funding: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2023-NR076807).
관련 논문AI추천
Corrigendum to: Optimization of Input Variables for Salinity Modeling in the Nakdong River Estuary Using Exploratory Data Analysis강지훈, 민수홍, 양정아, 윤종성, 이만득한국해양공학회 · 한국해양공학회지2025 · 제39권 제6호Random Forest Model for Salinity Prediction in the Nakdong River Estuary Reflecting Spatio-temporal Lag Effects강지훈, 김준헌, 민수홍, 윤종성한국해양공학회 · 한국해양공학회지2025 · 제39권 제4호Design and Application of a Physics-Informed Machine Learning Model for Salinity Prediction in the Nakdong River Estuary강지훈, 민수홍, 윤종성한국해양공학회 · 한국해양공학회지2025 · 제39권 제5호Optimization of Input Variables for Salinity Modeling in the Nakdong River Estuary Using Exploratory Data Analysis강지훈, 민수홍, 양정아, 윤종성, 이만득한국해양공학회 · 한국해양공학회지2025 · 제39권 제4호머신러닝 기법을 활용한 낙동강 하구 염분농도 예측이호준, 조민규, 천세진, 한정규(사)한국스마트미디어학회 · 스마트미디어저널2022 · 제11권 제2호시계열 분석 딥러닝 알고리즘을 적용한 낙동강 하굿둑 염분 예측김연중, 우정운, 윤종성한국해안,해양공학회 · 한국해안·해양공학회논문집2022 · 제34권 제4호
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