Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond

Research article (Transport Reviews, 2023) · cited 23× · AI/ML
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Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond

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Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond. Retrieved May 24, 2026, from https://4ort.xyz/entity/spatiotemporal-correlation-modelling-for-machine-learning-based-traffic-state-predictions-state-of-the-art-and-beyond
MLA “Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/spatiotemporal-correlation-modelling-for-machine-learning-based-traffic-state-predictions-state-of-the-art-and-beyond.
BibTeX @misc{4ortxyz_spatiotemporal-correlation-modelling-for-machine-learning-based-traffic-state-predictions-state-of-the-art-and-beyond_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Spatiotemporal correlation modelling for machine learning-based traffic state predictions: state-of-the-art and beyond}}, year = {2026}, url = {https://4ort.xyz/entity/spatiotemporal-correlation-modelling-for-machine-learning-based-traffic-state-predictions-state-of-the-art-and-beyond}, note = {Accessed: 2026-05-24}}
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