Home › Entities › academia › Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model

Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model

Research article (Sustainability, 2021) · cited 12× · AI/ML
academia openalex:W3122825272
Press Enter · cited answer in seconds

Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model

Summary

Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model is a scholarly article[1].

Key Facts

  • Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model's Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model — instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model. Retrieved May 24, 2026, from https://4ort.xyz/entity/spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw
MLA “Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw.
BibTeX @misc{4ortxyz_spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model}}, year = {2026}, url = {https://4ort.xyz/entity/spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Spatiotemporal Features—Extracted Travel Time Prediction Leveraging Deep-Learning-Enabled Graph Convolutional Neural Network Model — https://4ort.xyz/entity/spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/spatiotemporal-featuresextracted-travel-time-prediction-leveraging-deep-learning-enabled-graph-convolutional-neural-netw · Last refreshed: