Open AccessEstimation of Number of Flight Using Particle Swarm Optimization and Artificial Neural Network
Author(s) -
Ebru Pekel Özmen,
Engin Pekel
Publication year - 2019
Publication title -
advances in distributed computing and artificial intelligence journal
Language(s) - English
Resource type - Journals
ISSN - 2255-2863
DOI - 10.14201/adcaij2019832733
Subject(s) - particle swarm optimization , artificial neural network , correlation coefficient , swarm behaviour , computer science , artificial intelligence , mathematical optimization , mathematics , machine learning
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.