Multitype Origin-Destination (OD) Passenger Flow Prediction for Urban Rail Transit: A Deep Learning Clustering First Predicting Second Integrated Framework
Accurately predicting origin-destination (OD) passenger flows serves as the basis for implementing efficient plans, including line planning and timetabling. However, due to the complexity and variety of OD passenger flows types, general prediction models have difficulty in capturing the features of...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2024/6629500 |
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