A Spatiotemporal Convolutional Neural Network Model Based on Dual Attention Mechanism for Passenger Flow Prediction Article Swipe
Jinlong Li
,
Haoran Chen
,
Qiuzi Lu
,
Xi Wang
,
Haifeng Song
,
Lunming Qin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/math13142316
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/math13142316
Establishing a high-precision passenger flow prediction model is a critical and complex task for the optimization of urban rail transit systems. With the development of artificial intelligence technology, the data-driven technology has been widely studied in the intelligent transportation system. In this study, a neural network model based on the data-driven technology is established for the prediction of passenger flow in multiple urban rail transit stations to enable smart perception for optimizing urban railway transportation. The integration of network units with different specialities in the proposed model allows the network to capture passenger flow data, temporal correlation, spatial correlation, and spatiotemporal correlation with the dual attention mechanism, further improving the prediction accuracy. Experiments based on the actual passenger flow data of Beijing Metro Line 13 are conducted to compare the prediction performance of the proposed data-driven model with the other baseline models. The experimental results demonstrate that the proposed prediction model achieves lower MAE and RMSE in passenger flow prediction, and its fitted curve more closely aligns with the actual passenger flow data. This demonstrates the model’s practical potential to enhance intelligent transportation system management through more accurate passenger flow forecasting.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math13142316
- https://www.mdpi.com/2227-7390/13/14/2316/pdf?version=1753085124
- OA Status
- gold
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412515071
All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.3390/math13142316Digital Object Identifier
- Title
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A Spatiotemporal Convolutional Neural Network Model Based on Dual Attention Mechanism for Passenger Flow PredictionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-21Full publication date if available
- Authors
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Jinlong Li, Haoran Chen, Qiuzi Lu, Xi Wang, Haifeng Song, Lunming QinList of authors in order
- Landing page
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https://doi.org/10.3390/math13142316Publisher landing page
- PDF URL
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https://www.mdpi.com/2227-7390/13/14/2316/pdf?version=1753085124Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2227-7390/13/14/2316/pdf?version=1753085124Direct OA link when available
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Dual (grammatical number), Mechanism (biology), Convolutional neural network, Computer science, Flow (mathematics), Artificial intelligence, Mechanics, Physics, Art, Quantum mechanics, LiteratureTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| primary_location.raw_source_name | Mathematics |
| primary_location.landing_page_url | https://doi.org/10.3390/math13142316 |
| publication_date | 2025-07-21 |
| publication_year | 2025 |
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