A Study Of Predicting Arrival Patterns Of Airport Passengers To The Counters On The Basis Of International Terminal

AI-based passenger arrival predictions to the processing points are essential ensure efficient management of many intertwined operational processes in airport ecosystem. For example, be able analyze number ground service personnel that will required following hours, days different parts and for types operations, it is predict how passengers come time zones. Moreover, density-driven intelligent energy dynamic price offering options services could only generated with accurate predictions. Passenger arrivals can detected various technologies such as computer vision, IoT, lidar, radar. However, boarding pass printing event messages from CUPPS solution, which implemented İzmir Adnan Menderes Airport International Terminal, used data source this study. Also, Linear regression, FEDOT, LSTM, hybrid methods configured compared counts counters international terminal specified slots.