FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285295189> ?p ?o ?g. }

• W4285295189 endingPage "20216" @default.
• W4285295189 startingPage "20202" @default.
• W4285295189 abstract "Forecasting traffic inflows and outflows is crucial for intelligent transportation applications such as traffic management and risk assessment. Recently, deep learning models, which focus on capturing spatio-temporal correlations between stations (locations) by constructing Spatio-Temporal Feature Learners (STFL), have achieved promising performance in traffic inflows and outflows prediction. However, two unresolved issues limit the performance of these models. i) dynamic and heterogeneous intra- and inter-relationships between flows are ignored, and ii) the STFL in these models cannot capture the global information. To address the above issues, we propose a novel deep Spatio-Temporal Network framework based on Multi-Relational learning (MR-STN) for predicting traffic inflows and outflows. Specifically, a multi-relational learning module is designed to comprehensively model three kinds of relationships between flows while extracting diverse spatio-temporal features. In this module, an enhanced STFL is developed to capture both local and global information. Then, a feature fusion module is introduced to extract fused features for inflows and outflows respectively via a gated fusion mechanism. On this basis, the prediction module uses fusion features to generate future inflows and outflows. Finally, we implement the proposed framework with four state-of-the-art graph-based deep spatio-temporal models to demonstrate its generality and superiority. Extensive experiments on three datasets show that the proposed framework can significantly boost the performance of existing models." @default.
• W4285295189 created "2022-07-14" @default.
• W4285295189 creator A5005207362 @default.
• W4285295189 creator A5013548083 @default.
• W4285295189 creator A5016129617 @default.
• W4285295189 creator A5018065188 @default.
• W4285295189 creator A5018234604 @default.
• W4285295189 creator A5049828136 @default.
• W4285295189 creator A5051873858 @default.
• W4285295189 creator A5065949777 @default.
• W4285295189 creator A5090646680 @default.
• W4285295189 date "2022-11-01" @default.
• W4285295189 modified "2023-09-29" @default.
• W4285295189 title "Traffic Inflow and Outflow Forecasting by Modeling Intra- and Inter-Relationship Between Flows" @default.
• W4285295189 cites W1982978808 @default.
• W4285295189 cites W2004353783 @default.
• W4285295189 cites W2064675550 @default.
• W4285295189 cites W2108196201 @default.
• W4285295189 cites W2112796928 @default.
• W4285295189 cites W2150010190 @default.
• W4285295189 cites W2194775991 @default.
• W4285295189 cites W2528639018 @default.
• W4285295189 cites W2572939427 @default.
• W4285295189 cites W2573587735 @default.
• W4285295189 cites W2606105273 @default.
• W4285295189 cites W2788134583 @default.
• W4285295189 cites W2802508687 @default.
• W4285295189 cites W2901504064 @default.
• W4285295189 cites W2903871660 @default.
• W4285295189 cites W2910892140 @default.
• W4285295189 cites W2912985636 @default.
• W4285295189 cites W2945622688 @default.
• W4285295189 cites W2963091558 @default.
• W4285295189 cites W2963214893 @default.
• W4285295189 cites W2963240573 @default.
• W4285295189 cites W2965341826 @default.
• W4285295189 cites W2982310938 @default.
• W4285295189 cites W2996847713 @default.
• W4285295189 cites W2997848713 @default.
• W4285295189 cites W2998652672 @default.
• W4285295189 cites W3001314220 @default.
• W4285295189 cites W3012562343 @default.
• W4285295189 cites W3035580605 @default.
• W4285295189 cites W3080253043 @default.
• W4285295189 cites W3103720336 @default.
• W4285295189 cites W3109146615 @default.
• W4285295189 cites W3123191313 @default.
• W4285295189 cites W4249736682 @default.
• W4285295189 cites W2751650042 @default.
• W4285295189 doi "https://doi.org/10.1109/tits.2022.3187121" @default.
• W4285295189 hasPublicationYear "2022" @default.
• W4285295189 type Work @default.
• W4285295189 citedByCount "2" @default.
• W4285295189 countsByYear W42852951892023 @default.
• W4285295189 crossrefType "journal-article" @default.
• W4285295189 hasAuthorship W4285295189A5005207362 @default.
• W4285295189 hasAuthorship W4285295189A5013548083 @default.
• W4285295189 hasAuthorship W4285295189A5016129617 @default.
• W4285295189 hasAuthorship W4285295189A5018065188 @default.
• W4285295189 hasAuthorship W4285295189A5018234604 @default.
• W4285295189 hasAuthorship W4285295189A5049828136 @default.
• W4285295189 hasAuthorship W4285295189A5051873858 @default.
• W4285295189 hasAuthorship W4285295189A5065949777 @default.
• W4285295189 hasAuthorship W4285295189A5090646680 @default.
• W4285295189 hasConcept C108583219 @default.
• W4285295189 hasConcept C119857082 @default.
• W4285295189 hasConcept C124101348 @default.
• W4285295189 hasConcept C132525143 @default.
• W4285295189 hasConcept C138885662 @default.
• W4285295189 hasConcept C153294291 @default.
• W4285295189 hasConcept C154945302 @default.
• W4285295189 hasConcept C15744967 @default.
• W4285295189 hasConcept C205649164 @default.
• W4285295189 hasConcept C2776132308 @default.
• W4285295189 hasConcept C2776401178 @default.
• W4285295189 hasConcept C2780767217 @default.
• W4285295189 hasConcept C41008148 @default.
• W4285295189 hasConcept C41895202 @default.
• W4285295189 hasConcept C542102704 @default.
• W4285295189 hasConcept C80444323 @default.
• W4285295189 hasConceptScore W4285295189C108583219 @default.
• W4285295189 hasConceptScore W4285295189C119857082 @default.
• W4285295189 hasConceptScore W4285295189C124101348 @default.
• W4285295189 hasConceptScore W4285295189C132525143 @default.
• W4285295189 hasConceptScore W4285295189C138885662 @default.
• W4285295189 hasConceptScore W4285295189C153294291 @default.
• W4285295189 hasConceptScore W4285295189C154945302 @default.
• W4285295189 hasConceptScore W4285295189C15744967 @default.
• W4285295189 hasConceptScore W4285295189C205649164 @default.
• W4285295189 hasConceptScore W4285295189C2776132308 @default.
• W4285295189 hasConceptScore W4285295189C2776401178 @default.
• W4285295189 hasConceptScore W4285295189C2780767217 @default.
• W4285295189 hasConceptScore W4285295189C41008148 @default.
• W4285295189 hasConceptScore W4285295189C41895202 @default.
• W4285295189 hasConceptScore W4285295189C542102704 @default.
• W4285295189 hasConceptScore W4285295189C80444323 @default.
• W4285295189 hasFunder F4320335787 @default.
• W4285295189 hasIssue "11" @default.

• next