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Izvorni znanstveni članak
https://doi.org/10.7225/toms.v05.n02.001

Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities

Massimiliano Petri ; Dept. Civil and Industrial Engineering, University of Pisa, Pisa, Italy
Antonio Pratelli ; Dept. Civil and Industrial Engineering, University of Pisa, Pisa, Italy
Giovanni Fusco ; Centre National de la Recherche Scientifique, Université de Nice Sophia Antipolis, Nice, France

Puni tekst: engleski, pdf (974 KB) str. 99-110 preuzimanja: 507* citiraj
APA 6th Edition
Petri, M., Pratelli, A. i Fusco, G. (2016). Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities. Transactions on Maritime Science, 05 (02), 99-110. https://doi.org/10.7225/toms.v05.n02.001
MLA 8th Edition
Petri, Massimiliano, et al. "Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities." Transactions on Maritime Science, vol. 05, br. 02, 2016, str. 99-110. https://doi.org/10.7225/toms.v05.n02.001. Citirano 28.01.2020.
Chicago 17th Edition
Petri, Massimiliano, Antonio Pratelli i Giovanni Fusco. "Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities." Transactions on Maritime Science 05, br. 02 (2016): 99-110. https://doi.org/10.7225/toms.v05.n02.001
Harvard
Petri, M., Pratelli, A., i Fusco, G. (2016). 'Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities', Transactions on Maritime Science, 05(02), str. 99-110. https://doi.org/10.7225/toms.v05.n02.001
Vancouver
Petri M, Pratelli A, Fusco G. Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities. Transactions on Maritime Science [Internet]. 2016 [pristupljeno 28.01.2020.];05(02):99-110. https://doi.org/10.7225/toms.v05.n02.001
IEEE
M. Petri, A. Pratelli i G. Fusco, "Data Mining and Big Freight Transport Database Analysis and Forecasting Capabilities", Transactions on Maritime Science, vol.05, br. 02, str. 99-110, 2016. [Online]. https://doi.org/10.7225/toms.v05.n02.001

Sažetak
Transport modeling in general and freight transport modeling in particular are becoming important tools for investigating the effects of investments and policies. Freight demand forecasting models are still in an experimentation and evolution stage. Nevertheless, some recent European projects, like Transtools or ETIS/ETIS Plus, have developed a unique modeling and data framework for freight forecast at large scale so to avoid data availability and modeling problems. Despite this, important projects using these modeling frameworks have provided very different results for the same forecasting areas and years, giving rise to serious doubts about the results quality, especially in relation to their cost and development time. Moreover, many of these models are purely deterministic. The project described
in this article tries to overcome the above-mentioned problems with a new easy-to-implement freight demand forecasting method based on Bayesian Networks using European official and available data. The method is applied to the Transport Market study of the Sixth European Rail Freight Corridor.

Ključne riječi
Freight demand model; Bayesian networks; European freight corridor; Demand forecasting

Hrčak ID: 167821

URI
https://hrcak.srce.hr/167821

Posjeta: 721 *