Predicting Hourly Boarding Demand of Bus Passengers Using Imbalanced Records From Smart-Cards: A Deep Learning Approach (2023)
Attributed to:
NEXt generation activity and travel behavioUr modelS: Bringing together choice modelling, ubiquitous computing and data science
funded by
UKRI FLF
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.1109/tits.2023.3237134
Publication URI: http://dx.doi.org/10.1109/tits.2023.3237134
Type: Journal Article/Review
Parent Publication: IEEE Transactions on Intelligent Transportation Systems
Issue: 5