Mining Urban Traffic Hotspots and Analyzing Spatiotemporal Travel Demand of Residents Based on Clustering Algorithms—A Case Study of Taxi Trajectory Data in Chengdu. (2025). Statistics and Application, 14, 427-440. https://doi.org/10.12677/sa.2025.148247
ISO-690 (author-date, English)Mining Urban Traffic Hotspots and Analyzing Spatiotemporal Travel Demand of Residents Based on Clustering Algorithms—A Case Study of Taxi Trajectory Data in Chengdu, 2025. Statistics and Application. 1 January 2025. Vol. 14, , p. 427-440. DOI 10.12677/sa.2025.148247.
Modern Language Association 9th edition“Mining Urban Traffic Hotspots and Analyzing Spatiotemporal Travel Demand of Residents Based on Clustering Algorithms—A Case Study of Taxi Trajectory Data in Chengdu”. Statistics and Application, vol. 14, Jan. 2025, pp. 427-40, https://doi.org/10.12677/sa.2025.148247.
Mohr Siebeck - Recht (Deutsch - Österreich): Mining Urban Traffic Hotspots and Analyzing Spatiotemporal Travel Demand of Residents Based on Clustering Algorithms—A Case Study of Taxi Trajectory Data in Chengdu, Statistics and Application 2025, 427-440.
Emerald - Harvard“Mining Urban Traffic Hotspots and Analyzing Spatiotemporal Travel Demand of Residents Based on Clustering Algorithms—A Case Study of Taxi Trajectory Data in Chengdu”. (2025), Statistics and Application, Vol. 14, pp. 427-440.