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Neighborhood Crime and Non-Auto Mode Choice [PDF]
, 2008 Ferrell, Christopher +2 more
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Development of a ridership forecasting tool for small public transit systems using GIS [PDF]
, 2018 openaire +1 more source
Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic. [PDF]
PeerJSoucy JR +7 more
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Metro Ridership Forecasting using Inter-Station-Aware Transformer Networks
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023In recent years, the issue of predicting metro ridership has gained traction within the intelligent transportation systems community, due to its potential advantages for the metro network system such as improving the service quality and making informed ...
Khaled Saleh +2 more
semanticscholar +2 more sources
BARTNet: Context-Aware Deep Learning Framework for BART Ridership Forecasting
2025 IEEE Conference on Artificial Intelligence (CAI)In this paper, we propose a novel context-aware deep learning-based framework, BARTNet, for forecasting Bay Area Rapid Transit (BART) ridership by integrating contextual and temporal data.
Leela Sai Rahul Suryadevara +4 more
semanticscholar +2 more sources
Decision Tree Based Station-Level Rail Transit Ridership Forecasting
Journal of Urban Planning and Development, 2016AbstractThis paper presents a decision-tree based model to forecast rail transit ridership at the station level according to the surrounding land-use patterns. The canonical correlation analysis (CCA) method is used to identify key land use variables by evaluating their degrees of contribution to the rail transit station demand, which can effectively ...
Xin Li +3 more
semanticscholar +2 more sources
Seasonal decomposition and combination model for short-term forecasting of subway ridership
International Journal of Machine Learning and Cybernetics, 2021The subway ridership is related with the social activities, such as, commuting, festival, holiday, and so on, which makes the time series of subway ridership presents seasonal characteristic. This characteristic inspires us to decompose the time series into a seasonal component and an epoch component, and employ a combination forecasting method to ...
Jiqiang Tang +3 more
semanticscholar +2 more sources