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Hyeon‐Tae Moon

Observed names: Heyon-Tae Moon, Hyeon Tae Moon, Hyeon-Tae Moon, Hyeontae Moon, Moon, Hyeontae
ORCID: 0000-0002-3195-8751
Observed ORCID: 0000-0002-3195-8751
OpenAlex ID: A5048879769
Urban flood forecasting using a hybrid modeling approach based on a deep learning technique
2023 · Hyeontae Moon, Sunkwon Yoon, et al. · Journal of Hydroinformatics · 54
Mitigating urban flood Hazards: Hybrid strategy of structural measures
2024 · Hyeon-Tae Moon, Jong-Suk Kim, et al. · International Journal of Disaster Risk Reduction · 42
Integrated Flood Forecasting and Warning System against Flash Rainfall in the Small-Scaled Urban Stream
2020 · Jung Hwan Lee, Gi Moon Yuk, et al. · Atmosphere · 39
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Development and Application of an Urban Flood Forecasting and Warning Process to Reduce Urban Flood Damage: A Case Study of Dorim River Basin, Seoul
2022 · Yong-Man Won, Jung-Hwan Lee, et al. · Water · 36
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Assessing global drought conditions under climate change: A comparison of stationary and non-stationary approaches and identification of hotspot regions
2024 · Dian Wu, Jie Chen, et al. · Journal of Hydrology · 20
Assessing the Impact of Human-Induced and Climate Change-Driven Streamflow Alterations on Freshwater Ecosystems
2023 · Seo-Yeon Park, Hyeon-Tae Moon, et al. · Ecohydrology & Hydrobiology · 17
Drought Forecasting for Decision Makers Using Water Balance Analysis and Deep Neural Network
2022 · Ock-Jae Jang, Hyeon-Tae Moon, et al. · Water · 11
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Assessing future urban flood hazard: A comprehensive approach to estimating the implications of future rainfall scenarios
2024 · Hyeon‐Tae Moon, Sun‐Kwon Yoon, et al. · Journal of Flood Risk Management · 9
Flooding time nomograph for urban river flood prediction: Case study of Dorim stream basin, Seoul
2023 · Hyeontae Moon, Sunkwon Yoon, et al. · Journal of Flood Risk Management · 6
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Optimizing urban flood management: enhancing urban drainage system efficiency under extreme rainfall events
2024 · Tianfang Ma, Jong-Suk Kim, et al. · Journal of Hydroinformatics · 5
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Deep learning-enhanced flood damage prediction: A DFNN-based hybrid approach with simplified inputs
2025 · Ji-Yoon Mok, Hyeon-Tae Moon, et al. · International Journal of Disaster Risk Reduction · 4
Improving bathymetric mapping in shallow rivers: A Deep Feedforward Neural Network(DFNN) model for RGB-Based water depth prediction
2025 · Hyeontae Moon, Kyung-Tak Kim, et al. · Remote Sensing Applications Society and Environment · 1
Enhancing Urban Flood Resilience Through a Hybrid Approach Combining a Comprehensive Flood Prevention Plan (Cfpp) and Green Infrastructure (Gi)
2023 · Hyeontae Moon, Jong Suk Kim, et al. · SSRN Electronic Journal · 1
Diagnosing region-specific flood influencing factors in a volcanic island using explainable machine learning
2026 · Hyeontae Moon, Gilho Kim, et al. · Natural Hazards
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Enhancing urban flood risk assessment: A PCA-integrated deep learning surrogate for hazard and damage prediction
2026 · Hyeontae Moon, Kyung-Tak Kim, et al. · Water Research
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PCA-IDNN Urban Inundation Mapping Code
2026 · Moon, Hyeontae · Zenodo (CERN European Organization for Nuclear Research)
Data and Code Supporting "Enhancing Urban Flood Risk Assessment: A PCA-Integrated Deep Learning Surrogate for Hazard and Damage Prediction"
2026 · Moon, Hyeontae, Kim, Gilho · Zenodo (CERN European Organization for Nuclear Research)
Works count: 17
Citation count: 245
H-index: 8
I10-index: 7
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