6 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.LG2021
A Spatial-temporal Graph Deep Learning Model for Urban Flood Nowcasting Leveraging Heterogeneous Community Features
Hamed Farahmand, Yuanchang Xu, Ali Mostafavi
The objective of this study is to develop and test a novel structured deep-learning modeling framework for urban flood nowcasting by integrating physics-based and human-sensed feat…
physics.soc-ph2021★ 6 cited
Predicting Road Flooding Risk with Machine Learning Approaches Using Crowdsourced Reports and Fine-grained Traffic Data
Faxi Yuan, William Mobley, Hamed Farahmand +5
The objective of this study is to predict road flooding risks based on topographic, hydrologic, and temporal precipitation features using machine learning models. Predictive flood…
cs.LG2021★ 2 cited
Spatio-Temporal Graph Convolutional Networks for Road Network Inundation Status Prediction during Urban Flooding
Faxi Yuan, Yuanchang Xu, Qingchun Li +1
The objective of this study is to predict the near-future flooding status of road segments based on their own and adjacent road segments current status through the use of deep lear…