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). Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing. Retrieved May 24, 2026, from https://4ort.xyz/entity/efficient-deep-learning-based-method-for-multilane-speed-forecasting-a-case-study-in-beijing
MLA“Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/efficient-deep-learning-based-method-for-multilane-speed-forecasting-a-case-study-in-beijing.
BibTeX@misc{4ortxyz_efficient-deep-learning-based-method-for-multilane-speed-forecasting-a-case-study-in-beijing_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing}}, year = {2026}, url = {https://4ort.xyz/entity/efficient-deep-learning-based-method-for-multilane-speed-forecasting-a-case-study-in-beijing}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Efficient deep learning based method for multi‐lane speed forecasting: a case study in Beijing — https://4ort.xyz/entity/efficient-deep-learning-based-method-for-multilane-speed-forecasting-a-case-study-in-beijing (retrieved 2026-05-24)
