Clustered embedding using deep learning to analyze urban mobility based on complex transportation data.
Urban mobility is a vital aspect of any city and often influences its physical shape as well as its level of economic and social development. A thorough analysis of mobility patterns in urban areas can provide various benefits, such as the prediction of traffic flow and public transportation usage....
| Hlavní autoři: | , |
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| Médium: | Článek |
| Jazyk: | English |
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Public Library of Science (PLoS)
2021-01-01
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| Edice: | PLoS ONE |
| On-line přístup: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249318&type=printable |