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宏观交通运输系统的复杂度与可预测性 被引量:4

Analysis on Complexity and Predictability of Macroscopic Transportation System
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摘要 宏观交通运输系统复杂度与可预测性的关系需要定量描述。为测度宏观交通运输系统的复杂性,引入符号动力学的Lempel-Ziv算法。针对该算法的应用误区,提出改进的“通用试凑算法”。应用ARIMA模型,对宏观交通量时间序列进行模型估计和预测。计算5个实测时间序列的复杂度和预测误差,通过其结果比较,推论出一个假设:宏观交通运输系统的复杂度与可预测性存在负相关关系。 It is very important to quantificationally characterize the relationship between complexity and predictability of macroscopic transportation system.The Lempel-Ziv algorithm of symbolic dynamics has been introduced to measure the complexity of macroscopic transportation system.Aiming at the misapplications of this algorithm,the general method of trial and error is put forward.The ARIMA model has been applied to evaluate and predict the time series of macroscopic traffic volume.Complexity and prediction errors of 5 actual time series have been calculated.Based on the comparison of the calculated results,it is assumed that complexity is negatively correlated with predictability in macroscopic transportation system.
出处 《计算机工程与应用》 CSCD 北大核心 2006年第9期6-9,共4页 Computer Engineering and Applications
基金 国家自然科学基金资助项目(编号:50478088)
关键词 复杂度 预测 交通运输 Lempel-Ziv 算法 complexity, prediction, transportation, Lempel-Ziv algorithm
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参考文献10

  • 1Lempel A,Ziv J.On the complexity of finite sequences[J].IEEE Transactions on Information Theory,1976;IT-22(1):75~81
  • 2Kasper F,Schuster H G.Easily calculable mea-sure for the complexity of spatiotemporal patterns[J].Physical Review A,1987; 36 (2):842~848
  • 3Morita H,Kobayashi K.On asymptotic optimality of a sliding window variation of Lempel-Ziv codes[J].IEEE Transactions on Information Theory,1993 ;39(6):1840~1846
  • 4Radhakrishnan N,Gangadhar B N.Estimating regularity in epileptic seizure time-series data[J].IEEE Engineering in Medicine and Biology,1998; (3):.89~94
  • 5徐京华,吴祥宝.以复杂度测度刻划人脑皮层上的信息传输[J].中国科学(B辑),1994,24(1):57-62. 被引量:21
  • 6Jia W,Kong N,Li F et al.An epileptic seizure prediction algorithm based on second-order complexity measure[J].Physiological Measurement,2005; 26 (5):609~625
  • 7Chan H L,Lin M A,Fang S C.Linear and Nonlinear Analysis of Electroencephalogram of the Coma[C].In:Proceedings of the 26th Annual International Conference of the IEEE EMBS,2004:593~595
  • 8Yan R,Gao R X.Complexity as a Measure for Machine Health Evaluation[J].IEEE Transactions on instrumentation and measurement,2004;53(4):1327~1334
  • 9陈桂芬,邝慧,崔丽芳,张烈雄,林龙年.豚鼠听神经放电的复杂性分析[J].生物物理学报,2003,19(3):297-302. 被引量:2
  • 10中国经济信息网[EB/OL].http://www.cei.gov.cn/index/Transform.asp?cedb = 7&ThreeBlockCode = 030701&Template = dbjjnj027&blockcode =DBjjnj_ys,2005 -07 -01

二级参考文献18

  • 1Liberman MC. Ultrastructural differences among afferent synapses on cochlear hair cells: correlations with spontaneous discharge rate. J Comp Neurol, 1996,371:208-221.
  • 2Liberman MC. Single neuron labelling in the cat auditory nerve. Science, 1982,216:1239-1241.
  • 3Alder VA, Johnstone BM. A new approach to the guinea pig auditory nerve. J Acount Soc Am, 1978,64:684---687.
  • 4Pincus S. Approximate entropy (ApEn) as a complexity measure. Chaos, 1995,5:110-117.
  • 5Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA, 1991,88:2297-2301.
  • 6Zhang XS, Roy ILl, Jensen EW. EEG complexity as a measure of depth of anesthesia for patients. IEEE Tram Biomed Eng, 2001,48:1424-1433.
  • 7Gusev VD, Kulichkov VA, Chupakhina OM. The Lempel-Ziv complexity and local structure analysis of genomes.Biosystems, 1993,30:183-200.
  • 8Stern L, Allison L, Coppel R.L, Dix TI. Discovering patterns in plasmodium falciparurn genomic DNA. Mol Biochem Parasitol, 2001,118:175-186.
  • 9Zhang XS, Zhu YS, Zhang XJ. New approach to studies on ECG dynamics: Extraction and analyses of QRS complex irregularity time series. Med Biol Eng Comput, 1997,35:467--474.
  • 10Zhang XS, Roy ILl. Predicting movement during anesthesia by complexity analysis of the EEG. Med Biol Eng Comput,1999,37:327-334.

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