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