Short-term traffic flow prediction based on ratio-median lengths of intervals two-factors high-order fuzzy time series

2007 IEEE International Conference on Vehicular Electronics and Safety, ICVES

Volumn , Issue , 2007, Pages

  Zhao, Liang ^b   Wang, Fei Yue ^a,b,c  

^a IEEE

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c University of Arizona   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHLORINE COMPOUNDS; FOOD PROCESSING; FORECASTING; MATHEMATICAL MODELS; REGRESSION ANALYSIS; THREE TERM CONTROL SYSTEMS; TIME SERIES ANALYSIS; TRAFFIC SURVEYS;

BEIJING; FUZZY TIME SERIES PREDICTION; FUZZY TIME-SERIES; HIGH-ORDER; INTERNATIONAL CONFERENCES; LINGUISTIC VARIABLES; PREDICTION ACCURACY; PREDICTION MODELING; SHORT-TERM TRAFFIC FLOW; STATISTICAL REGRESSION MODELS; TRAFFIC FLOW CHARACTERISTICS; TRAFFIC FLOW PREDICTION; TRAFFIC FLOWING; UNIVERSE OF DISCOURSE; VEHICULAR ELECTRONICS;

TRAFFIC CONTROL;

EID: 50249111530     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICVES.2007.4456387     Document Type: Conference Paper

References (32)

1. Sen. A., Sööt. S., Ligas. J. and Tian. X., "Arterial link travel time estimation: probes, detectors and assignment-type models." Preprints of papers at the Transportation Research Board 76th Annual meeting, Washington, D.C., pp. 21 1997.
2. Ben-Akiva. M., Cascetta. E. and Gunn. H. "An on-line dynamic traffic prediction model for an inter-urban motorway network." Urban Traffic Networks:Dynamic Flow Modeling and Control, Gartner, N. H. and Improta, G. (eds.), New York: Springer-Verlag, pp. 83-122, 1995.
3. Smith. B. L. and Demetsky. M. J.,"Traffic flow forecasting: comparison of modeling approaches." Journal of Transportation Engineering, vol. 123, no. 4, p.261-266, 1997.
4. Kaysi. I., Ben-Akiva. M., and Koutsopoulos. H.,"An integrated approach to vehicle routing and congestion prediction for real-time driver guidance." Transportation Research Record 1408, TRB, Washington, D.C., pp. 66-74,1993.
5. Hobeika A.G,Chang kyun Kim,"Traffic-flow-prediction system based on upstream traffic [A]". Vehical Navigation and Information System Conference [C],1994.
6. Ben-Akiva. M., Cascetta. E. and Whittaker. J., "Recent progress in short-range traffic prediction." Compendium of Technical Papers, Institute of Transportation Engineers (ITE), pp. 262-265,1993.
7. Dochy. T., Danech-Pajouh. M. and Lechevallier. Y. "Short-term road forecasting using neural network." Recherche-Transports-Securite, English issue, no. 11, pp. 73-82,1995.
8. Palacharla. P. V. and Nelson. P. C. "On-line travel time estimation using fuzzy neural network." Proceedings of 1995 ITS World Congress,Yokohama,Japan, pp.112-116,1995.
9. Chai Quek,Michel Pasquier and Bernard Boon Seng Lim,"POPTRAFFIC: a novel fuzzy neural approach to road traffic analysis and prediction," IEEE Trans. Intelligent Transportation Systems, vol.7, no.2, pp. 133-146, Jun. 2006.
10. Hongbin Yin,S.C.Wong,Jianmin Xu,C.K.Wong,"Urban traffic flow prediction using a fuzzy-neural approach," Transportation Research Part C, vol.10,pp.85-98, 2002.
11. Davis, G. A. and Nihan, N. L. "Nonparametric regression and shortterm freeway traffic forecasting." Journal of Transportation Engineering, pp. 178-188,1991.
12. H. T. Nguyen and B.Wu, Fuzzy Mathematics andStatistical Applications, Taipei, Taiwan: Wu Nan Company, 2000.
13. F.-M. Tseng, G.-H. Tzeng, H.-C. Yu, and B. J. C. Yuan, Fuzzy ARIMA model for forecasting the foreign exchange market, Fuzzy Sets Syst., vol. 118, no. 1, pp. 9-19, Feb. 2001.
14. S.-M. Chen,Forecasting enrollments based on fuzzy time series, Fuzzy Sets Syst., vol. 81, no. 3, pp. 311-319, Aug. 1996.
15. K.Huarng, Heuristic models of fuzzy time series for forecasting, Fuzzy Sets Syst., vol. 123, no. 3, pp. 369-386, Nov. 2001.
16. K. Huarng, Effective lengths of intervals to improve forecasting in fuzzy time series, Fuzzy Sets Syst., vol. 123, no. 3, pp. 387-394, Nov. 2001.
17. K. Huarng and H.-K. Yu, Ratio-based lengths of intervals to improve fuzzy time series forecasting, IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 36, no. 2, pp. 328-340, Apr. 2006.
18. J. R. Hwang, S.-M. Chen, and C.-H. Lee, Handling forecasting problems using fuzzy time series, Fuzzy Sets Syst., vol. 100, no. 1-3, pp. 217-228, Nov. 1998.
19. Q. Song and B. S. Chissom, Forecasting enrollments with fuzzy time series-Part 1, Fuzzy Sets Syst., vol. 54, no. 1, pp. 1-9, Jan. 1993.
20. Q. Song and B. S. Chissom, Forecasting enrollments with fuzzy time series-Part 2, Fuzzy Sets Syst., vol. 62, no. 1, pp. 1-8, Feb. 1994.
21. J. Sullivan and W. H. Woodall, A comparison of fuzzy forecasting and Markov modeling, Fuzzy Sets Syst., vol. 64, no. 3, pp. 279C293, Jun. 1994.
22. S.-M. Chen and J. R. Hwang, Temperature prediction using fuzzy time series, IEEE Trans. Syst., Man, Cybern. B, vol. 30, no. 2, pp. 263-275, Apr. 2000.
23. K. Huarng and H.-K. Yu, A dynamic approach to adjusting lengths of intervals in fuzzy time series forecasting, Intell. Data Anal., vol. 8, no. 1, pp. 3-27, 2004.
24. K. Huarng and H.-K. Yu, A type 2 fuzzy time series model for stock index forecasting, Physica A, vol. 353, pp. 445-462, Aug. 2005.
25. H.-K. Yu, A refined fuzzy time-series model for forecasting, Physica A, vol. 346, no. 3/4, pp. 657-681, Feb. 2005.
26. H.-K. Yu, Weighted fuzzy time series models for TAIEX forecasting, Physica A, vol. 349, no. 3/4, pp. 609-624, Apr. 2005.
27. Y.-Y. Hsu, S.-M. Tse, and B. Wu, A new approach of bivariate fuzzy time series analysis to the forecasting of a stock index, Int. J. Uncertain. Fuzziness Knowl.-BasedSyst. , vol. 6, no. 11, pp. 671-690, 2003.
28. Q. Song and B. S. Chissom, Fuzzy time series and its models, Fuzzy Sets Syst., vol. 54, no. 3, pp. 269-277, 1993.
29. Sheng-Tun Li and Yeh-Peng Chen,"Natural partitioning-based forecasting model for fuzzy time-series," Proc. FUZZY-IEEE, Budapest, Hungary, pp. 1355-1359, Jul. 2004.
30. Li-wei Lee a, Li-hui Wang b, Shyi-ming Chen,"Temperature prediction and TAIFEX forecasting based on fuzzy logical relationships and genetic algorithms,"Expert Systems with Applications, vol. 33, pp. 539-550, 2007.
31. Li-wei Lee, Li-hui Wang, Shyi-ming Chen,"Temperature prediction and TAIFEX forecasting based on high-order fuzzy logical relationships and genetic simulated annealing techniques,"Expert Systems with Applications, 2006.
32. Li-wei Lee, Li-hui Wang, Shyi-ming Chen and Yung-ho Leu,"Handling forecasting problems based on two-factors highorder fuzzy time series"IEEE Trans. Fuzzy Syst., vol. 14, no. 3, Jun. 2006.