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A Support Vector Machine Approach for Effective Bicycle Sharing in Urban Zones
4 references·1 citing·21 second hop
A Support Vector Machine Approach for Effective Bicycle Sharing in Urban Zones (2021)A Support Vector Machine Approach for Eff…A Hierarchical Demand Prediction Method with Station Clustering for Bike Sharing System (2018)A Hierarchical Demand Predict…A forecast for bicycle rental demand based on random forests and multiple linear regression (2017)A forecast for bicycle rental…Traffic prediction in a bike-sharing system (2015)Traffic prediction in a bike-…Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto (2015)Effects of built environment …MHA: Mobile Application-Based Analysis of Mental Disorders (2024)MHA: Mobile Application-Based…Travel and the Built Environment: A Synthesis (2001)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Environmental benefits of bike sharing: A big data-based analysis (2018)A review on bike-sharing: The factors affecting bike-sharing demand (2019)Built environment effects on the integration of dockless bike-sharing and the metro (2020)Bikesharing in Europe, the Americas, and Asia (2010)Urban cycles and mobility patterns: Exploring and predicting trends in a bicycle-based public transport system (2010)Dynamic cluster-based over-demand prediction in bike sharing systems (2016)Rebalancing Bike Sharing Systems (2016)Planning Bike Lanes based on Sharing-Bikes' Trajectories (2017)Sensing and predicting the pulse of the city through shared bicycling (2009)Demand Prediction and Optimal Allocation of Shared Bikes Around Urban Rail Transit Stations (2022)Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach (2022)Cross-Mode Knowledge Adaptation for Bike Sharing Demand Prediction Using Domain-Adversarial Graph Neural Networks (2023)Mobile phones as medical devices in mental disorder treatment: an overview (2014)A Systematic Review of Cognitive Behavioral Therapy and Behavioral Activation Apps for Depression (2016)Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning (2017)Season wise bike sharing demand analysis using random forest algorithm (2020)Machine Learning Approaches to Bike-Sharing Systems: A Systematic Literature Review (2021)The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods (2022)
this work references cited by second hop

References

  • 2015Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto570 cited
  • 2015Traffic prediction in a bike-sharing system361 cited
  • 2017A forecast for bicycle rental demand based on random forests and multiple linear regression71 cited
  • 2018A Hierarchical Demand Prediction Method with Station Clustering for Bike Sharing System45 cited

Cited by

  • 2024MHA: Mobile Application-Based Analysis of Mental Disorders5 cited

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