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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2017  >  17(1): 109-118
ZHANG Ming-yang, ZHANG Di, GUO Huan, FU Shan-shan, HUANG Ya-min. Complexity metric of waterborne traffic flow based on Lempel-Ziv algorithm and TOPSIS[J]. Journal of Traffic and Transportation Engineering, 2017, 17(1): 109-118.
Citation: ZHANG Ming-yang, ZHANG Di, GUO Huan, FU Shan-shan, HUANG Ya-min. Complexity metric of waterborne traffic flow based on Lempel-Ziv algorithm and TOPSIS[J]. Journal of Traffic and Transportation Engineering, 2017, 17(1): 109-118.
shu

Complexity metric of waterborne traffic flow based on Lempel-Ziv algorithm and TOPSIS

  • 1.

    Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan 430063, Hubei, China

  • 2.

    National Engineering Research Center for Water Transport Safety, Wuhan 430063, Hubei, China

  • 3.

    School of Mathematics and Computer Science, Jianghan University, Wuhan 430056, Hubei, China

  • 4.

    School of Technology, Policy and Management, Delft University of Technology, Delft 2600AA, South Holland, Netherlands

More Information
  • Author Bio:

    ZHANG Ming-yang(1993-), male, doctoral student, +86-27-86581997, mingyang-zhang@whut.edu.cn

    ZHANG Di(1983-), male, associate professor, PhD, +86-27-86581997, zhangdi@whut.edu.cn

  • Received Date: 2016-08-11
  • Publish Date: 2017-02-25
    Abstract
  • In order to quantitatively analyze and classify waterborne traffic flow complexity, a method of waterborne traffic flow complexity metric was proposed based on Lempel-Ziv algorithm and TOPSIS (technique for order preference by similarity to an ideal solution).Firstly, LempelZiv algorithm was used to obtain the complexity eigenvalues of measured time sequences ofwaterborne traffic flow and other compared sequences (periodic sequence, logistic sequence, Henon sequence and random sequence).Secondly, the close degree of each sequence was calculated by using TOPSIS.The class of complexity was divided by those close degrees of compared sequences.At last, the complexity degree of each sequence was represented by close degrees of time sequences of waterborne traffic flow and the complexity class.This complexity metric was carried out on the waterborne traffic flow of south channel of the Yangtze River.Calculation result shows that the correlation coefficient of complexity close degree of waterborne ship traffic flow is 0.698 1 with the number of ship traffic accidents, and 0.769 2 with the downside traffic flow of standard ships, respectively.The change trend is basically consistent, so the complexity close degree can reflect the complexity of waterborne ship traffic flow.The close degrees of periodic sequence and random sequence are 0.000 1 and 0.999 9, respectively.Meanwhile, the close degrees of logistic sequence and Henon sequence are 0.449 2 and 0.537 7, respectively.The close degrees of logistic sequence and Henon sequence are greater than periodic sequence and and less than random sequence.The close degrees of waterborne traffic flow from July to November in 2013 are 0.828 0, 0.852 7, 0.856 5, 0.823 7 and 0.810 7, respectively, the complexity of waterborne traffic flow is basically consistent.The values of waterborne traffic flow are far greater than those of periodic sequence, locate between the values of Henon sequence and random sequence, and are closer to the value of random sequence, which shows that the waterborne traffic system is neither periodic nor completely stochastic.The complexity class of time sequence of waterborne traffic flow is Level 1, showing high complexity.

     

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