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Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory

Research article (GIScience & Remote Sensing, 2023) · cited 10× · AI/ML
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Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory

Summary

Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory is a scholarly article[1].

Key Facts

  • Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory. Retrieved May 24, 2026, from https://4ort.xyz/entity/diagnosing-urban-traffic-anomalies-by-integrating-geographic-knowledge-and-tensor-theory
MLA “Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/diagnosing-urban-traffic-anomalies-by-integrating-geographic-knowledge-and-tensor-theory.
BibTeX @misc{4ortxyz_diagnosing-urban-traffic-anomalies-by-integrating-geographic-knowledge-and-tensor-theory_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory}}, year = {2026}, url = {https://4ort.xyz/entity/diagnosing-urban-traffic-anomalies-by-integrating-geographic-knowledge-and-tensor-theory}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory — https://4ort.xyz/entity/diagnosing-urban-traffic-anomalies-by-integrating-geographic-knowledge-and-tensor-theory (retrieved 2026-05-24)

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