Matches in SemOpenAlex for { <https://semopenalex.org/work/W4310854593> ?p ?o ?g. }
Showing items 1 to 71 of
71
with 100 items per page.
- W4310854593 abstract "Taxi is an important component of the urban transport system in most cities. Accurate taxi demand prediction can effectively reduce the waiting time of passengers and shorten the no-load travel of drivers, which is helpful in alleviating traffic congestion and improving traffic efficiency. Due to the complexity of the traffic system and spatiotemporal dependencies among regions in a road network, traditional prediction methods cannot predict taxi demands of different regions effectively. This paper introduces a Graph Multi-Attention Network (GMAN) to handle the taxi demand prediction problem with better performance, which aims to predict the taxi demands in all regions of a road network in the next time period. The effectiveness of the GMAN is validated based on a large-scale dataset of taxi demands from a real urban road network. Experimental results show that the GMAN outperforms 5 commonly used benchmarking models, including 3 state-of-the-art machine learning models." @default.
- W4310854593 created "2022-12-19" @default.
- W4310854593 creator A5037691746 @default.
- W4310854593 creator A5060739855 @default.
- W4310854593 creator A5063670849 @default.
- W4310854593 date "2022-10-28" @default.
- W4310854593 modified "2023-09-23" @default.
- W4310854593 title "Graph Multi-Attention Network-based Taxi Demand Prediction" @default.
- W4310854593 cites W101796584 @default.
- W4310854593 cites W2069143585 @default.
- W4310854593 cites W2162550419 @default.
- W4310854593 cites W2766311542 @default.
- W4310854593 cites W2788134583 @default.
- W4310854593 cites W2889260000 @default.
- W4310854593 cites W2891773644 @default.
- W4310854593 cites W2906175158 @default.
- W4310854593 cites W2962756421 @default.
- W4310854593 cites W2997848713 @default.
- W4310854593 cites W3013365237 @default.
- W4310854593 cites W3091801004 @default.
- W4310854593 cites W3103720336 @default.
- W4310854593 doi "https://doi.org/10.1109/docs55193.2022.9967748" @default.
- W4310854593 hasPublicationYear "2022" @default.
- W4310854593 type Work @default.
- W4310854593 citedByCount "0" @default.
- W4310854593 crossrefType "proceedings-article" @default.
- W4310854593 hasAuthorship W4310854593A5037691746 @default.
- W4310854593 hasAuthorship W4310854593A5060739855 @default.
- W4310854593 hasAuthorship W4310854593A5063670849 @default.
- W4310854593 hasConcept C121332964 @default.
- W4310854593 hasConcept C127413603 @default.
- W4310854593 hasConcept C132525143 @default.
- W4310854593 hasConcept C144133560 @default.
- W4310854593 hasConcept C162853370 @default.
- W4310854593 hasConcept C168167062 @default.
- W4310854593 hasConcept C22212356 @default.
- W4310854593 hasConcept C2779888511 @default.
- W4310854593 hasConcept C41008148 @default.
- W4310854593 hasConcept C80444323 @default.
- W4310854593 hasConcept C86251818 @default.
- W4310854593 hasConcept C97355855 @default.
- W4310854593 hasConceptScore W4310854593C121332964 @default.
- W4310854593 hasConceptScore W4310854593C127413603 @default.
- W4310854593 hasConceptScore W4310854593C132525143 @default.
- W4310854593 hasConceptScore W4310854593C144133560 @default.
- W4310854593 hasConceptScore W4310854593C162853370 @default.
- W4310854593 hasConceptScore W4310854593C168167062 @default.
- W4310854593 hasConceptScore W4310854593C22212356 @default.
- W4310854593 hasConceptScore W4310854593C2779888511 @default.
- W4310854593 hasConceptScore W4310854593C41008148 @default.
- W4310854593 hasConceptScore W4310854593C80444323 @default.
- W4310854593 hasConceptScore W4310854593C86251818 @default.
- W4310854593 hasConceptScore W4310854593C97355855 @default.
- W4310854593 hasFunder F4320321001 @default.
- W4310854593 hasFunder F4320322990 @default.
- W4310854593 hasLocation W43108545931 @default.
- W4310854593 hasOpenAccess W4310854593 @default.
- W4310854593 hasPrimaryLocation W43108545931 @default.
- W4310854593 hasRelatedWork W1532309383 @default.
- W4310854593 hasRelatedWork W1537716277 @default.
- W4310854593 hasRelatedWork W1636112402 @default.
- W4310854593 hasRelatedWork W172869079 @default.
- W4310854593 hasRelatedWork W2155350564 @default.
- W4310854593 hasRelatedWork W2379533788 @default.
- W4310854593 hasRelatedWork W3009603553 @default.
- W4310854593 hasRelatedWork W4206693874 @default.
- W4310854593 hasRelatedWork W593909985 @default.
- W4310854593 hasRelatedWork W833284001 @default.
- W4310854593 isParatext "false" @default.
- W4310854593 isRetracted "false" @default.
- W4310854593 workType "article" @default.