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Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations
Research article (Engineering Applications of Artificial Intelligence, 2023) · cited 25× · AI/ML
Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations
Summary
Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations is a scholarly article[1].
Key Facts
Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations'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). Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations. Retrieved May 24, 2026, from https://4ort.xyz/entity/robust-spatiotemporal-crash-risk-prediction-with-gated-recurrent-convolution-network-and-interpretable-insights-from-sha
MLA“Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/robust-spatiotemporal-crash-risk-prediction-with-gated-recurrent-convolution-network-and-interpretable-insights-from-sha.
BibTeX@misc{4ortxyz_robust-spatiotemporal-crash-risk-prediction-with-gated-recurrent-convolution-network-and-interpretable-insights-from-sha_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations}}, year = {2026}, url = {https://4ort.xyz/entity/robust-spatiotemporal-crash-risk-prediction-with-gated-recurrent-convolution-network-and-interpretable-insights-from-sha}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Robust spatiotemporal crash risk prediction with gated recurrent convolution network and interpretable insights from SHapley additive explanations — https://4ort.xyz/entity/robust-spatiotemporal-crash-risk-prediction-with-gated-recurrent-convolution-network-and-interpretable-insights-from-sha (retrieved 2026-05-24)
