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20202026
most citedExamining spatial heterogeneity of ridesourcing demand determinants with explainable machine learning

34 citations · 50 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023

Causality-informed Rapid Post-hurricane Building Damage Detection in Large Scale from InSAR Imagery

Chenguang Wang, Yepeng Liu, Xiaojian Zhang +6

Timely and accurate assessment of hurricane-induced building damage is crucial for effective post-hurricane response and recovery efforts. Recently, remote sensing technologies pro…

cs.LG2023★ 3 cited

Situational-Aware Multi-Graph Convolutional Recurrent Network (SA-MGCRN) for Travel Demand Forecasting During Wildfires

Xiaojian Zhang, Xilei Zhao, Yiming Xu +2

Real-time forecasting of travel demand during wildfire evacuations is crucial for emergency managers and transportation planners to make timely and better-informed decisions. Howev…

cs.LG2023

Travel Demand Forecasting: A Fair AI Approach

Xiaojian Zhang, Qian Ke, Xilei Zhao

Artificial Intelligence (AI) and machine learning have been increasingly adopted for travel demand forecasting. The AI-based travel demand forecasting models, though generate accur…

cs.LG2022★ 34 cited

Examining spatial heterogeneity of ridesourcing demand determinants with explainable machine learning

Xiaojian Zhang, Xiang Yan, Zhengze Zhou +2

The growing significance of ridesourcing services in recent years suggests a need to examine the key determinants of ridesourcing demand. However, little is known regarding the non…

cs.LG2021★ 1 cited

A Clustering-aided Ensemble Method for Predicting Ridesourcing Demand in Chicago

Xiaojian Zhang, Xilei Zhao

Accurately forecasting ridesourcing demand is important for effective transportation planning and policy-making. With the rise of Artificial Intelligence (AI), researchers have sta…