Home ›
Entities
› academia
› A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction
A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction
Research article (IET Intelligent Transport Systems, 2022) · cited 21× · AI/ML
A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction
Summary
A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction is a scholarly article[1].
Key Facts
A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-multiattention-dynamic-graph-convolution-network-with-costsensitive-learning-approach-to-roadlevel-and-minutelevel-tra
MLA“A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-multiattention-dynamic-graph-convolution-network-with-costsensitive-learning-approach-to-roadlevel-and-minutelevel-tra.
BibTeX@misc{4ortxyz_a-multiattention-dynamic-graph-convolution-network-with-costsensitive-learning-approach-to-roadlevel-and-minutelevel-tra_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction}}, year = {2026}, url = {https://4ort.xyz/entity/a-multiattention-dynamic-graph-convolution-network-with-costsensitive-learning-approach-to-roadlevel-and-minutelevel-tra}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction — https://4ort.xyz/entity/a-multiattention-dynamic-graph-convolution-network-with-costsensitive-learning-approach-to-roadlevel-and-minutelevel-tra (retrieved 2026-05-24)
