Dynamic Graph Convolutional Network-Based Prediction of the Urban Grid-Level Taxi Demand–Supply Imba...
Dynamic Graph Convolutional Network-Based Prediction of the Urban Grid-Level Taxi Demand–Supply Imbalance Using GPS Trajectories
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The application of Graph Convolutional Networks (GCNs) in traffic forecasting has inspired the develop...
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Dynamic Graph Convolutional Network-Based Prediction of the Urban Grid-Level Taxi Demand–Supply Imbalance Using GPS Trajectories
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TN_cdi_doaj_primary_oai_doaj_org_article_10e07444cf304ed7af50b37847a268d7
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_10e07444cf304ed7af50b37847a268d7
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ISSN
2220-9964
E-ISSN
2220-9964
DOI
10.3390/ijgi13020034
