Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 422-424.doi: 10.11896/j.issn.1002-137X.2016.6A.100

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Computational Model of Average Travel Speed Based on K-means Algorithms

GAO Man, HAN Yong, CHEN Ge, ZHANG Xiao-lei and LI Jie   

  • Online:2018-11-14 Published:2018-11-14

Abstract: It is possible to retrieve real-time data using floating bus data acquisition system equipped with positioning and wireless communication apparatus.To explore traffic condition,a data fusion model based on the K-means clustering algorithm was put forward.The model was used to calculate the average travel speed between adjacent bus stops.At first,K-means clustering algorithm was improved:(1)the cluster number K is not predefined but the square root of non-identical sample size,and it is different at different sections and time;(2)the initial cluster center is not random but selected according to K.Then,the sample data were divided into K classes by the improved algorithm and the average travel speed was obtained by data fusion model.Finally,the average travel speed of four areas in Qingdao was shown by line charts to explore some evolution law of traffic flow.The research provides strong support for traffic management and residents travel.

Key words: Public transport,Average travel speed,K-means clustering algorithms,Data fusion,Data mining

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