计算机应用研究2012，Vol.29Issue(4)：1263-1266,4.DOI:10.3969/j.issn.1001-3695.2012.04.017
基于FCM城市区域道路交通状态时空分层判别方法
Spatial and temporal model for urban regional traffic state analysis based on fuzzy C-means clustering
摘要
Abstract
This paper developed a spatial and temporal hierarchical model based on fuzzy C-means clustering for area traffic state analysis to predict area traffic states. Firstly, it quantitatively analyzed the traffic state of the unit of the road network. Then gained the cluster centers of each traffic state for the unit of the road network based on the method of fuzzy C-means clustering. After this.it recognized and classified the real-time traffic state combining its real-time traffic data. According the units' space distribution in the network, the model presented the different kinds of spatial distribution under different traffic states. The result of example proves that this analytical method obtain the spatial and temporal traffic state accurately. It also supplies the assistant decision-making information for transportation system managers.关键词
交通状态/时空分析/模糊C均值聚类Key words
traffic state/ temporal and spatial analysis/ fuzzy C-means clustering分类
交通工程引用本文复制引用
董红召,马帅,郭明飞..基于FCM城市区域道路交通状态时空分层判别方法[J].计算机应用研究,2012,29(4):1263-1266,4.基金项目
国家自然科学基金资助项目(61174176) （61174176）
浙江省科技公益项目(2010C33245) （2010C33245）
特种装备制造与先进加工技术教育部/浙江省重点实验室开放基金 （）
杭州市社会发展科研专项资助项目(20110533B02) （20110533B02）
