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김동균 프로필 사진

김동균

Kim, Dong Kyun

공과대학

건설환경공학과

연도별 연구 활동 현황

전체 132건 중 21번부터 30번까지의 결과를 표시합니다.

2025

Article

Streamflow forecasting in ungauged basins with CNN-LSTM and radar-based precipitation (vol. 60, 100666, 2025)

Article

Streamflow forecasting in ungauged basins with CNN-LSTM and radar-based precipitation

Article

Beneath the surface: Exploring relationship between pluvial floods and income disparities for residential basements in Seoul, South Korea

Article

Impact of climatic factors on eutrophication in the World's largest lake

Article

Hydrologic risk assessment of drought in South Korea according to climate change scenarios using a multiple drought index integrated with a dynamic naive Bayesian classifier

Article

A reassessment of the history of the temporal resolution of rainfall data at the global scale

Article

A novel deep learning-based approach for reconstruction of historical long-term high-quality gridded meteorological dataset

Article

Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorithms

Article

Rainfall nowcasting models: state of the art and possible future perspectives

Article

Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms

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김동균

자료유형

발행연도

키워드

언어

Streamflow forecasting in ungauged basins with CNN-LSTM and radar-based precipitation (vol. 60, 100666, 2025)

Streamflow forecasting in ungauged basins with CNN-LSTM and radar-based precipitation

Beneath the surface: Exploring relationship between pluvial floods and income disparities for residential basements in Seoul, South Korea

Impact of climatic factors on eutrophication in the World's largest lake

Hydrologic risk assessment of drought in South Korea according to climate change scenarios using a multiple drought index integrated with a dynamic naive Bayesian classifier

A reassessment of the history of the temporal resolution of rainfall data at the global scale

A novel deep learning-based approach for reconstruction of historical long-term high-quality gridded meteorological dataset

Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorithms

Rainfall nowcasting models: state of the art and possible future perspectives

Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms