DocumentCode :
3730368
Title :
Fuzzy c-means clustering identification method of urban road traffic state
Author :
Guangyu Zhu; Jianjun Chen; Peng Zhang
Author_Institution :
MOE Key Laboratory for Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, China 100044
fYear :
2015
Firstpage :
302
Lastpage :
307
Abstract :
Urban road state identification refers to determining the operation status of the road network system, which plays an important role in urban road traffic management. By clustering time series of traffic flow, typical fluctuation pattern recognize algorithms of traffic flow can get the urban road network operation states. As the detected traffic data contain vague and uncertain information, preprocessing is needed. An improved fuzzy c-means clustering (FCM) method is proposed in this paper. A case study based on urban road section of Beijing City demonstrates the feasibility and effectiveness of the improved FCM algorithm.
Keywords :
"Clustering algorithms","Roads","Algorithm design and analysis","Indexes","Classification algorithms","Linear programming"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
Type :
conf
DOI :
10.1109/FSKD.2015.7381958
Filename :
7381958
Link To Document :
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