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Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China
Research article (Sustainability, 2018) · cited 21× · AI/ML
Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China
Summary
Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China is a scholarly article[1].
Key Facts
Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China'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). Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/identification-of-vehicle-pedestrian-collision-hotspots-at-the-micro-level-using-network-kernel-density-estimation-and-r
MLA“Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/identification-of-vehicle-pedestrian-collision-hotspots-at-the-micro-level-using-network-kernel-density-estimation-and-r.
BibTeX@misc{4ortxyz_identification-of-vehicle-pedestrian-collision-hotspots-at-the-micro-level-using-network-kernel-density-estimation-and-r_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China}}, year = {2026}, url = {https://4ort.xyz/entity/identification-of-vehicle-pedestrian-collision-hotspots-at-the-micro-level-using-network-kernel-density-estimation-and-r}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China — https://4ort.xyz/entity/identification-of-vehicle-pedestrian-collision-hotspots-at-the-micro-level-using-network-kernel-density-estimation-and-r (retrieved 2026-05-24)
