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Impact of COVID-19 pandemic on low-carbon shared traffic scheduling under machine learning model
The present work aims to expand the application of machine learning models in predicting and identifying traffic flow data and provide a reference for the scheduling and management of shared traffic against the Coronavirus Disease 2019 (COVID-19) pandemic. First, a time segmentation-based prediction...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer India
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231089/ http://dx.doi.org/10.1007/s13198-021-01176-x |