A Hybrid Neural Network Prediction Model of Air Ticket Sales

Abstract

Air ticket sales revenue is an important source of revenue for travel agencies, and if future air ticket sales revenue can be accurately forecast, travel agencies will be able to advance procurement to achieve a sufficient amount of cost-effective tickets. Therefore, this study applied the Artificial Neural Network (ANN) and Genetic Algorithms (GA) to establish a prediction model of travel agency air ticket sales revenue. By verifying the empirical data, this study proved that the established prediction model has accurate prediction power, and MAPE (mean absolute percentage error) is only 9.11%. The established model can provide business operators with reliable and efficient prediction data as a reference for operational decisions. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.2762