Abstract
With the continuous development of data mining technology, to apply the data mining techniques to transportation sector will provide service to transportation scientifically and reasonably. In intelligent transportation, the analysis of traffic flow data is very important, how to analyze the traffic data intelligently is more difficult problem, so using a new data mining techniques to replace the traditional data analysis and interpretation methods is very necessary and meaningful, clustering algorithm is the collection of physical or abstracting objects into groups of similar objects from the multiple classes of processes. This paper describes all kinds of the data mining clustering algorithms, clustering algorithm is proposed in the method of dealing with traffic flow data, and applied to the actual traffic data processing, and finally the clustering algorithm is applied to each of highway toll station Various types of car traffic volume data analysis.
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© 2011 Springer-Verlag Berlin Heidelberg
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Qiong, L., Jie, Y., Jinfang, Z. (2011). Application of Clustering Algorithm in Intelligent Transportation Data Analysis. In: Zhu, M. (eds) Information and Management Engineering. ICCIC 2011. Communications in Computer and Information Science, vol 236. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24097-3_70
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DOI: https://doi.org/10.1007/978-3-642-24097-3_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24096-6
Online ISBN: 978-3-642-24097-3
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