A Machine Learning-Based 10 Years Ahead Prediction of Departing Foreign Visitors by Reasons: A Case on Türkiye

The most important underlying reasons for marketing failures are incomplete understanding of customer wants and needs the inability to accurately predict their future behaviors. This study develops a machine learning model estimate number departing foreign visitors from Türkiye by next 10 years gain deeper data between 2003 2021 extensively analyzed, multi-dimensional having higher-order fractional-order polynomial structure is constructed. resulting can update predictions every year as new becomes available it has stable parameters. In addition, batch-type genetic algorithm modified learn unknown parameters considering disruptions, such coup attempt in 2016 COVID-19 pandemic outbreak 2019, termed uncertainties. Thus, overall behavior presence uncertainties, which dominant character reasons. Furthermore, developed utterly data-driven, meaning be trained with collected different cities, regions, countries. It predicted that all will increase at various rates 2022 2031, while transit higher than others. results discussed, suggestions given science. helpful global local firms tourism, governmental agencies, civil society organizations.