Transport Choice Modeling for the Evaluation of New Transport Policies
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @Article{su10041230,
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author = "Ander Pijoan and Oihane Kamara-Esteban and
Ainhoa Alonso-Vicario and Cruz E. Borges",
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title = "Transport Choice Modeling for the Evaluation of New
Transport Policies",
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journal = "Sustainability",
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volume = "10",
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year = "2018",
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number = "4",
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article_number = "1230",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "2071-1050",
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URL = "http://www.mdpi.com/2071-1050/10/4/1230",
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DOI = "doi:10.3390/su10041230",
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abstract = "Quantifying the impact of the application of
sustainable transport policies is essential in order to
mitigate effects of greenhouse gas emissions produced
by the transport sector. One of the most common
approaches used for this purpose is that of traffic
modelling and simulation, which consists of emulating
the operation of an entire road network. This article
presents the results of fitting 8 well known data
science methods for transport choice modelling, the
area in which more research is needed. The models have
been trained with information from Biscay province in
Spain in order to match as many of its commuters as
possible. Results show that the best models correctly
forecast more than 51percent of the trips recorded.
Finally, the results have been validated with a second
data set from the Silesian Voivodeship in Poland,
showing that all models indeed maintain their
forecasting ability.",
- }
Genetic Programming entries for
Ander Pijoan
Oihane Kamara-Esteban
Ainhoa Alonso-Vicario
Cruz Enrique Borges
Citations