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Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies
Research article (Engineering Applications of Artificial Intelligence, 2023) · cited 16× · AI/ML
Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies
Summary
Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies is a scholarly article[1].
Key Facts
Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies. Retrieved May 24, 2026, from https://4ort.xyz/entity/adaboosting-graph-attention-recurrent-network-a-deep-learning-framework-for-traffic-speed-forecasting-in-dynamic-transpo
MLA“Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/adaboosting-graph-attention-recurrent-network-a-deep-learning-framework-for-traffic-speed-forecasting-in-dynamic-transpo.
BibTeX@misc{4ortxyz_adaboosting-graph-attention-recurrent-network-a-deep-learning-framework-for-traffic-speed-forecasting-in-dynamic-transpo_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies}}, year = {2026}, url = {https://4ort.xyz/entity/adaboosting-graph-attention-recurrent-network-a-deep-learning-framework-for-traffic-speed-forecasting-in-dynamic-transpo}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Adaboosting graph attention recurrent network: A deep learning framework for traffic speed forecasting in dynamic transportation networks with spatial-temporal dependencies — https://4ort.xyz/entity/adaboosting-graph-attention-recurrent-network-a-deep-learning-framework-for-traffic-speed-forecasting-in-dynamic-transpo (retrieved 2026-05-24)
