Title :
Traffic status evaluation based on fuzzy clustering and rbf neural network
Author :
Xiaofeng Liu ; Sun, D. ; Yuntao Chang ; Zhongren Peng
Author_Institution :
Sch. of Transp. Eng., Tongji Univ., Shanghai, China
Abstract :
This paper introduces the C-means fuzzy clustering method to evaluate the road traffic status. During the analysis, road traffic status was categorized into four types by using ISODATA algorithm based on expert knowledge. Meanwhile, RBF neural network classification model was established to evaluate the road traffic status. The implementation results showed that the proposed method was capable of evaluating road traffic status, and reflecting the related quantitative fluctuations.
Keywords :
fuzzy set theory; pattern clustering; radial basis function networks; road traffic; traffic engineering computing; C-means fuzzy clustering method; ISODATA algorithm; RBF neural network classification model; expert knowledge; road traffic status evaluation; Algorithm design and analysis; Artificial neural networks; Classification algorithms; Clustering algorithms; Data models; Probes; Roads; ISODATA algorithm; RBF neural network; Road traffic status evaluation; fuzzy C-means clustering; traffic congestion;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569188
