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Dynamic
forecasting of traffic volume based on quantificational
dynamics: A nearness perspective
Yan-hong Tang* and Bao Xi
School of Management, Harbin Institute of Technology,
150001, Harbin, China.
*Corresponding author. E-mail:
tangyanhong@yahoo.cn,
tyh119@126.com.
Accepted 21 January, 2010 |
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Accurate and timely forecasting of traffic volume has long
been regarded as a key point in transportation, planning
and management. In order to realize effective and efficient
traffic forecasting, this paper investigates
quantificational method of dynamic factors from the
perspective of nearness. The dynamic modeling method based
on quantificational dynamics (that is, quantificational
disposal of dynamic factors according to nearness) is
proposed and this method can significantly improve the
forecast effectiveness and efficiency. Swarm simulation is
adopted as a new tool with regard to the field of traffic
forecasting for analysis and verification. The testing
results show that the proposed method outperforms
traditional ones in choosing training samples and
constituting forecasting models. This work contributes to
the consideration and evaluation of dynamic factors in
scientific forecasting and may bring some enlightenment to
relevant scientific researchers and engineers.
Key words:
Traffic forecasting, dynamic factors, quantificational
dynamics, nearness, swarm simulation. |
