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RUI Hai-tian, WU Qun-qi, YUAN Hua-zhi, FENG Zhong-xiang, ZHU Wen-ying. Prediction method of highway passenger transportation volume based on exponential smoothing method and Markov model[J]. Journal of Traffic and Transportation Engineering, 2013, 13(4): 87-93. doi: 10.19818/j.cnki.1671-1637.2013.04.013
Citation: RUI Hai-tian, WU Qun-qi, YUAN Hua-zhi, FENG Zhong-xiang, ZHU Wen-ying. Prediction method of highway passenger transportation volume based on exponential smoothing method and Markov model[J]. Journal of Traffic and Transportation Engineering, 2013, 13(4): 87-93. doi: 10.19818/j.cnki.1671-1637.2013.04.013
shu

Prediction method of highway passenger transportation volume based on exponential smoothing method and Markov model

doi: 10.19818/j.cnki.1671-1637.2013.04.013
  • 1.

    School of Economics and Management, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China

  • 3.

    School of Transportation Engineering, Hefei Univesity of Technology, Hefei 230009, Anhui, China

More Information
  • Author Bio:

    RUI Hai-tian(1973-), male, doctoral student, +86-29-82334385, rht1973@chd.edu.cn

    WU Qun-qi(1956-), male, professor, PhD, +86-29-82334528, wqq@chd.edu.cn

  • Received Date: 2013-01-18
  • Publish Date: 2013-08-25
    Abstract
  • The usual prediction methods of passenger transportation volume were analyzed, a new prediction method of highway passenger transportation volume based on exponential smoothing method and Markov model was put out. Based on the actual value, linear fitting value and quadratic curve fitting value of highway passenger transportation volume, the initial value and smoothing coefficient were calculated by using quadratic curve fitting method. According to the related data of Anhui Province in 2000-2009, the highway passenger transportation volumes in 2010, 2011 were predicted by using exponential smoothing method. Taking -11%, -5%, 0, 5%, 11% as division threshold values, the relative errors of prediction results by using exponential smoothing method were divided into four state intervals, the prediction results of exponential smoothing method were modified by using Markov model, and the prediction results among the proposed method, fuzzy linear regession model and exponential smoothing method were compared. Analysis result shows that by using the proposed method, the prediction results of highway passenger transportation volumes in 2010, 2011 are 1.420 9×1010, 1.571 2×1010 persons, relative errors are 1.195% and 0.492% respectively. By using exponential smoothing method, prediction results are 1.346 8×1010, 1.489 3×1010 persons, relative errors are -3.399% and -4.746% respectively. By using fuzzy linear regession model, prediction results are 1.357 3×1010, 1.532 5×1010 persons, relative errors are -2.647% and -1.983% respectively. The proposed method has higher precision to meet the actical demands.

     

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    • References(23)
  • [1]
    GARRIDO R A, MAHMASSNI H S. Forecasting freight transportation demand with the space-time multinomial probit model[J]. Transportation Research Part B: Methodological, 2000, 34 (5): 403-418. doi: 10.1016/S0191-2615(99)00032-6
    [2]
    GODFREY G A, POWELL W B. An adaptive dynamic programming algorithm for dynamic fleet management, Ⅱ: multiperiod travel times[J]. Transportation Science, 2002, 36 (1): 40-54. doi: 10.1287/trsc.36.1.40.572
    [3]
    DANTAS A, YAMAMOTO K, LAMAR M V, et al. Neural network for ravel demand forecast using GIS and remote sensing[C]//University of Canterbury. Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. Como: University of Canterbury, 2000: 435-440.
    [4]
    CHIOU H K, TZENG G H, CHENG C K, et al. Grey prediction model for forecasting the planning material of equipment spare parts in navy of Taiwan[C]//National Chiao Tung University. Proceedings of the 5th Word Automation Congress. Hsinchu: National Chiao Tung University, 2004: 315-320.
    [5]
    SURYANI E, CHOU S Y, CHEN C H. Air passenger demand forecasting and passenger terminal capacity expansion: a system dynamics framework[J]. Expert Systems with Applications, 2010, 37 (3): 2324-2339. doi: 10.1016/j.eswa.2009.07.041
    [6]
    PENG Hui, WEI Jin-li, CHEN Kuan-min. Construction of OD model of middle and long distance highway trips and prediction of segment passenger volume of transport corridor[J]. China Journal of Highway and Transport, 2006, 19 (2): 101-105. (in Chinese). doi: 10.3321/j.issn:1001-7372.2006.02.018
    [7]
    LI Ming-wei, KANG Hai-gui, ZHOU Peng-fei. Urban passenger prediction based on hybrid algorithm of new chaos accelerating genetic algorithm and PPPR model[J]. Systems Engineering—Theory and Practice, 2012, 32 (4): 903-910. (in Chinese). doi: 10.3969/j.issn.1000-6788.2012.04.029
    [8]
    CHEN Peng, SUN Quan-xin. Study of railway passenger volume forecast method based on grey-Markov process[J]. Railway Transport and Economy, 2005, 27 (4): 65-67. (inChinese). doi: 10.3969/j.issn.1003-1421.2005.04.026
    [9]
    WU Wei, FU Zhuo, WANG Xiao. Passenger volume forecast method for transport corridor[J]. Journal of Railway Science and Engineering, 2012, 9 (5): 96-102. (in Chinese). doi: 10.3969/j.issn.1672-7029.2012.05.018
    [10]
    WANG Yu-ping, MA Chao-qun. Influencing factors and development trends of urban rail transit passenger flow[J]. Journal of Chang'an University: Natural Science Edition, 2013, 33 (3): 69-75. (in Chinese). doi: 10.3969/j.issn.1671-8879.2013.03.012
    [11]
    HUNG Bang-ju, LIN Jun-song, ZHENG Xiao-yu, et al. The prediction for civil airport passenger throughput based on multiple linear regression analysis[J]. Mathematics in Practice and Theory, 2013, 43 (4): 172-178. (in Chinese). doi: 10.3969/j.issn.1000-0984.2013.04.025
    [12]
    ZHAO Jian-you, ZHOU Sun-feng, CUI Xiao-juan, et al. Predictive method oh highway freight volume based on fuzzy linear regession model[J]. Journal of Traffic and Transportation Engineering, 2012, 12 (3): 80-85. (in Chinese). doi: 10.3969/j.issn.1671-1637.2012.03.014
    [13]
    ZHAO Shu-zhi, TIAN Zhen-zhong, ZHANG Shu-shan, et al. Combination forecast model by using BP neural network and its application in highway transportation volume forecast[J]. Journal of Transportation Systems Engineering and Information Technology, 2006, 6 (4): 108-112. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT200604021.htm
    [14]
    SUN Xu, LU Hua-pu, WU Juan. Passenger traffic volume forecasting based on support vector machine model optimized by ant colony algorithm[J]. Journal of Hefei University of Technology: Natural Science, 2012, 35 (1): 124-129. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HEFE201201032.htm
    [15]
    WEI Yan-qiang, LIU Hai-lin, NING Hong-yun. Measure-ment study of highway transportation volume forecast based on RBF neural network[J]. Journal of Tianjin University of Technology, 2008, 24 (1): 17-20. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TEAR200801005.htm
    [16]
    TIAN Zhi-hui, WANG Shi-jie. Research on the forecast of the highway traffic volume based on the theory of the four stages forecast[J]. Journal of Zhengzhou University: Engineering Science, 2008, 29 (3): 133-136. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZZGY200803033.htm
    [17]
    MA Xiao-ke, WANG Ci-guang. The application of the cubic exponential smoothing method on volume forecasting of Da-Qin Railway[J]. Journal of East China Jiaotong University, 2005, 22 (3): 8-11. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HDJT200503003.htm
    [18]
    MALYSHKINA N V, MANNERING F L. Markov switching multinomial logit model: an application to accident-injury severities[J]. Accident Analysis and Prevention, 2009, 41 (4): 829-838.
    [19]
    RABINER L R. A tutorial on hidden Markov models and selected applications in speech recognition[J]. Proceedings of the IEEE, 1989, 77 (2): 257-286.
    [20]
    RABINER L R, JUANG B H. An introduction to hidden Markov models[J]. IEEE ASSP Magazine, 1986, 3 (1): 4-16.
    [21]
    REN Qi-liang. Study on application of grey-Markov model to forecasting elastic coefficients in highway transportation volume[J]. Journal of Chongqing Jiaotong University: Natural science, 2009, 28 (2): 290-293. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT200902031.htm
    [22]
    LI Da-wei, XU Hao-jun, LIU Dong-liang, et al. Improved grey Markov model and its application in prediction of flight accident rate[J]. China Safety Science Journal, 2009, 19 (9): 53-57. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK200909011.htm
    [23]
    LU An, HU Zhen-cheng, CHEN Hui. Recognition and analysis on highway overtaking behavior based on Gaussian mixture-hidden Markov model[J]. Automotive Engineering, 2010, 32 (7): 630-634. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201007019.htm
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