CNN2D Based Model for Prediction of Hourly Boarding Demand of Bus Passengers using Imbalanced Records from Smart-Cards

Authors

  • Mr K.Jummelal, Bhavana Vemparala , K.Naga Sahithi, B.Prathyusha

Keywords:

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Abstract

An invaluable resource for understandingpassenger boarding patterns and forecasting
future travel demand is the tap-on smart-carddata. Positive instances,

References

X. Guo, J. Wu, H. Sun, R. Liu, and Z. Gao, “Timetable coordination of first trains

in urban railway network: A case study of Beijing,” Applied Mathematical Modelling, vol. 40, no. 17, pp. 8048–8066, 2016.

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Published

2024-01-02

How to Cite

Mr K.Jummelal, Bhavana Vemparala , K.Naga Sahithi, B.Prathyusha. (2024). CNN2D Based Model for Prediction of Hourly Boarding Demand of Bus Passengers using Imbalanced Records from Smart-Cards . Journal of Computational Analysis and Applications (JoCAAA), 32(1), 764–774. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2683

Issue

Vol. 32 No. 1 (2024): JOCAAA

Section

Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.