基于Lempel-Ziv算法与TOPSIS的水上交通流复杂性测度

为了定量分析并划分水上交通流的复杂性等级, 提出了一种基于Lempel-Ziv算法与TOPSIS的水上交通流复杂性测度方法。运用Lempel-Ziv算法求得实测水上交通流时间序列和对比序列(周期序列、Logistic序列、Henon序列、随机序列) 的复杂性特征值, 采用TOPSIS得到各个序列的贴近度, 根据对比序列的贴近度划分复杂性等级区间, 按照水上交通流时间序列的贴近度和所在的复杂性等级区间来表征各个序列的复杂程度, 并对长江口南槽航道的实测水上交通流进行复杂性测度。计算结果表明: 船舶交通事故数量和下行标准船舶数量与船舶交通流时序复杂性贴近度的相关系数分别为0.698 1、0.769 2, 变化趋势基本一致, 表明贴近度的计算结果可以反映水域船舶交通流的复杂性; 周期序列的贴近度为0.000 1, 随机序列的贴近度为0.999 9, Logistic序列和Henon序列的贴近度分别为0.449 2、0.537 7, 其值大于周期序列的贴近度, 小于随机序列的贴近度; 2013年7~11月水上交通流序列的贴近度分别为0.828 0、0.852 7、0.856 5、0.823 7、0.810 7, 说明序列的复杂性基本一致; 5个月的水上交通流序列的贴近度远大于周期序列的贴近度, 处于随机序列和Henon序列的贴近度之间, 更接近随机序列的贴近度, 说明水上交通流系统不是周期与完全随机的动力学系统; 5个月水上交通流复杂性的整体等级为1级, 表现出高复杂性的特点。

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

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.