|Table of Contents|

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

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年04期
Page:
87-93
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Prediction method of highway passenger transportation volume based on exponential smoothing method and Markov model
Author(s):
RUI Hai-tian1 WU Qun-qi1 YUAN Hua-zhi2 FENG Zhong-xiang3 ZHU Wen-ying1
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
Keywords:
traffic planning highway passenger transportation volume prediction method exponential smoothing method Markov model fuzzy linear regression model
PACS:
U491.1
DOI:
-
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. 7 tabs, 1 fig, 23 refs.

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Last Update: 2013-08-30