2026-09-16T19:56:29Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1433122025-06-05T12:36:20Zcom_10366_142734com_10366_122682com_10366_4666com_10366_3823col_10366_143230

00925njm 22002777a 4500 dc Pekel Özmen, Ebru author Pekel, Engin author 2019-09-14 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. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8 (2019) 2255-2863 http://hdl.handle.net/10366/143312 Computación Informótica Computing Information Technology Estimation of Number of Flight Using Particle Swarm Optimization and Artificial Neural Network