Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

Interpretable machine-learning models for estimating trip purpose in smart card data

7 references·9 citing·49 second hop

FromToDepth

this work references cited by second hop

References

2013Mining smart card data for transit riders’ travel patterns606 cited
2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
2014Behavioural data mining of transit smart card data: A data fusion approach278 cited
2018Public transport trip purpose inference using smart card fare data160 cited
2013Trip purpose inference using automated fare collection data122 cited
2015Activity imputation for trip-chains elicited from smart-card data using a continuous hidden Markov model97 cited
2013Daily activity pattern recognition by using support vector machines with multiple classes95 cited

Cited by

2023Machine Learning Applied to Public Transportation by Bus: A Systematic Literature Review21 cited
2020Development of a Model for Evaluating the Coverage Area of Transit Center Using Smart Card Data14 cited
2022Activity-based TOD typology for seoul transit station areas using smart-card data13 cited
2022Predicting customer purpose of travel in a low-cost travel environment—A Machine Learning Approach12 cited
2025Collaborative generative adversarial networks for fusing household travel survey and smart card data to generate heterogeneous activity schedules in urban digital twins11 cited
2024Unveiling mobility patterns beyond home/work activities: A topic modeling approach using transit smart card and land-use data

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

8 cited

2023Enriching smart card data with the trip purpose attribute4 cited

2023Inferring alighting bus stops from smart card data combined with cellular signaling data4 cited

2024Converting Urban Trips to Multi-Dimensional Signals to Improve Trip Purpose Inference3 cited