天津建设科技2026，Vol.36Issue(3)：1-5,5.DOI:10.3969/j.issn.1008-3197.2026.03.001
基于数据融合的高速公路用户画像及聚类分析
Identification of Expressway User Groups:Clustering and Portrait Analysis Based on K-means
郭甲 1王楠 2胡封疆 3曾磊2
作者信息
- 1. 山东建筑大学 交通工程学院,山东 济南 250000
- 2. 天津高速公路集团有限公司,天津 300384
- 3. 天津市政工程设计研究总院有限公司,天津 300392
- 折叠
摘要
Abstract
To address the challenges of complex and diverse travel behaviors of freight vehicles in Tianjin and the lack of clear user identification,a comprehensive dataset integrating data from the Tianjin Expressway system and a freight logistics platform was constructed,containing multi-dimensional attributes including vehicle trajecto-ry,vehicle type,and registration location.Data cleaning,matching,and integration were performed on the Python platform.The K-means clustering algorithm was applied for unsupervised learning on high-dimension-al feature vectors,and a relatively high K value was set to enable fine-grained travel pattern recognition.This approach effectively reveals the travel diver.关键词
数据融合/聚类算法/用户画像/高速公路Key words
data fusion/clustering algorithm/user profiling/expressway分类
交通工程引用本文复制引用
郭甲,王楠,胡封疆,曾磊..基于数据融合的高速公路用户画像及聚类分析[J].天津建设科技,2026,36(3):1-5,5.
