Machine learning framework to estimate ridership loss in public transport during external crises: case study of bus network in Stockholm
Abstract Recent technologies for recording and storing data, as well as advancements in data processing techniques, have opened up novel possibilities for urban planners to design a more optimal public transport network. This study aims to initially develop a robust framework for making an insightfu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
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| Series: | European Transport Research Review |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12544-025-00722-z |
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