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

2019 Advances in Distributed Computing and Artificial Intelligence Journal  
artificial neural network; airport; particle swarm optimization; estimation 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
more » ... 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.
doi:10.14201/adcaij2019832733 fatcat:ckslvbu5lzesxgrq6dzanoflg4