Abstract
The paper proposes a GM (1, N) model for urban automobile detection demand forecast, which lays the foundation for the planning of detection site capability as well as the site network. The paper considers the automobile detection regulation, and takes the vehicle ownership in each class basing on the detection rule as the input variables. The grey incidence analysis is applied to determine the variables to employ, and then build up the GM (1, N) model for vehicle detection demand forecast. The efficiency of model is validated with the data of the City of Tianjin.
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Notes
- 1.
The number of vehicles which should have been inspected according to the regulation of the inspection cycle.
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Acknowledgment
The Project is supported by National Natural Science Foundation of China (GrantNo.70971094, Grant No.50908155).
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Xie, G., Wang, Gc., Ma, Sf. (2013). A Forecasting Model for the Detection Demand of Automobiles. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of 20th International Conference on Industrial Engineering and Engineering Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40072-8_10
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DOI: https://doi.org/10.1007/978-3-642-40072-8_10
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