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2013 | OriginalPaper | Buchkapitel

A Forecasting Model for the Detection Demand of Automobiles

verfasst von : Gang Xie, Guang-chao Wang, Shou-feng Ma

Erschienen in: Proceedings of 20th International Conference on Industrial Engineering and Engineering Management

Verlag: Springer Berlin Heidelberg

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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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Fußnoten
1
The number of vehicles which should have been inspected according to the regulation of the inspection cycle.
 
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Metadaten
Titel
A Forecasting Model for the Detection Demand of Automobiles
verfasst von
Gang Xie
Guang-chao Wang
Shou-feng Ma
Copyright-Jahr
2013
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-40072-8_10