A computational intelligence-based approach for short-term traffic flow prediction
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @Article{Zargari:2012:ES,
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author = "Shahriar Afandizadeh Zargari and
Salar Zabihi Siabil and Amir Hossein Alavi and Amir Hossein Gandomi",
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title = "A computational intelligence-based approach for
short-term traffic flow prediction",
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journal = "Expert Systems",
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year = "2012",
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volume = "29",
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number = "2",
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pages = "124--142",
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month = may,
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keywords = "genetic algorithms, genetic programming, Discipulus,
traffic flow, prediction, artificial neural network,
fuzzy logic, formulation",
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ISSN = "1468-0394",
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URL = "http://onlinelibrary.wiley.com/doi/10.1111/j.1468-0394.2010.00567.x/abstract",
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DOI = "doi:10.1111/j.1468-0394.2010.00567.x",
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size = "18.1 pages",
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abstract = "This paper proposes alternative approaches for the
prediction of short-term traffic flow using three
branches of computational intelligence techniques,
namely linear genetic programming (LGP), multilayer
perceptron (MLP) and fuzzy logic (FL). Different LGP,
MLP and FL models are developed for estimating the 5-
and 30-min traffic flow rates. New LGP- and MLP-based
prediction equations are derived for the traffic flow
rates in the five and thirty minute time intervals. The
models are established upon extensive databases of the
traffic flow records obtained from Iran's Rasht-Qazvin
highway. The results indicate that the proposed models
are effectively capable of predicting the target
values. The LGP-based models are found to be simple,
straightforward and more practical for predictive
purposes compared with the other derived models.",
- }
Genetic Programming entries for
Shahriar Afandizadeh Zargari
Salar Zabihi Siabil
A H Alavi
A H Gandomi
Citations