Estimation of Number of Flight Using Particle Swarm Optimization and Artificial Neural Network

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ISSN online: 2255-2863

Prefijo Doi: 10.14201

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Ebru Pekel Özmen
Istanbul University-Cerrahpasa
Turkey
Engin Pekel
Hitit University
Turkey
Vol. 8 No. 3 (2019), Articles, pages 27-33
DOI: https://doi.org/10.14201/ADCAIJ2019832733
Accepted: Feb 25, 2020
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Abstract

The number of flight (NF) is one of the key factors for the administration of the airport to evaluate the apron capacity and airline companies to fix the size of the flight. This paper aims to estimate the monthly NF by performing particle swarm optimization (PSO) and artificial neural network (ANN). Performed PSO-ANN algorithm aims to minimize the proposed evaluation criterion in the training stage. PSO-ANN based on the proposed evaluation criterion offers satisfying fitness values with respect to correlation coefficient and mean absolute percentage error in the training and testing stage.

Keywords:

artificial neural network, airport, particle swarm optimization, estimation

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References

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