2 citations · 4 across the 5 of their papers we have counts for
5 papers
Comparative Analysis of Polygon-Based and Global Machine Learning Models for Bus Occupancy Prediction
Daniel Azenkot, Michael Fire, Eran Ben Elia
Accurate forecasting of bus ridership (passengers numbers) is crucial for efficient management and optimization of public transport systems. Traditional forecasting models often fa…
A Comprehensive Machine Learning Framework for Micromobility Demand Prediction
Omri Porat, Michael Fire, Eran Ben-Elia
Dockless e-scooters, a key micromobility service, have emerged as eco-friendly and flexible urban transport alternatives. These services improve first and last-mile connectivity, r…
Short Run Transit Route Planning Decision Support System Using a Deep Learning-Based Weighted Graph
Nadav Shalit, Michael Fire, Dima Kagan +1
Public transport routing plays a crucial role in transit network design, ensuring a satisfactory level of service for passengers. However, current routing solutions rely on traditi…
Microtransit adoption in the wake of the COVID-19 pandemic: evidence from a choice experiment with transit and car commuters
Jason Soria, Shelly Etzioni, Yoram Shiftan +2
On-demand mobility platforms play an increasingly important role in urban mobility systems. Impacts are still debated, as these platforms supply personalized and optimized services…
A Supervised Machine Learning Model For Imputing Missing Boarding Stops In Smart Card Data
Nadav Shalit, Michael Fire, Eran Ben-Elia
Public transport has become an essential part of urban existence with increased population densities and environmental awareness. Large quantities of data are currently generated,…