A computational intelligence-based approach for short-term traffic flow prediction

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@Article{Zargari:2012:ES,

• author = "Shahriar Afandizadeh Zargari and Salar Zabihi Siabil and Amir Hossein Alavi and Amir Hossein Gandomi",
• title = "A computational intelligence-based approach for short-term traffic flow prediction",
• journal = "Expert Systems",
• year = "2012",
• volume = "29",
• number = "2",
• pages = "124--142",
• month = may,
• keywords = "genetic algorithms, genetic programming, Discipulus, traffic flow, prediction, artificial neural network, fuzzy logic, formulation",
• ISSN = "1468-0394",
• URL = "http://onlinelibrary.wiley.com/doi/10.1111/j.1468-0394.2010.00567.x/abstract",
• DOI = "doi:10.1111/j.1468-0394.2010.00567.x",
• size = "18.1 pages",
• 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