# Demand Forecasting Model for Airline Flights Based on Historical Passenger Flow Data
## 1 Introduction  
The attainment of an effective management system within the air transport industry has become increasingly challenging as a result of several factors, including the intrinsic complexity of the systems themselves, the multitude of interrelationships between processes, and the prevalence of external uncertainty. The development of predictive models to assess the operational and financial performance of air transport companies is becoming a topic of considerable interest within the research community [1]. This involves the use of complex mathematical models that consider a multitude of factors influencing performance, including passenger demand dynamics, fuel consumption, airfares, and the condition of the aircraft fleet [2; 3; 4]. The development of numerical mathematical models in the air transport industry has been employed to address a range of challenges, including forecasting passenger demand for air travel and short-term flight bookings [5], predicting the distribution of passenger traffic in airport terminals [6], estimating airport delays [7], and estimating passenger load factors for flight service planning and inventory management decisions [8].  
Nevertheless, it is the passenger demand estimation model and its accuracy that are of paramount importance for the rational planning of industry resources. The solution to this problem entails the identification of the factors affecting changes in air travel demand, an assessment of their extent of influence, and the selection of appropriate forecasting methods and tools [9]. The factors affecting final demand may be related to the pricing policies of airlines operating in the market under consideration, to a class of social influences, such as the average per capita income of the population of the departure and arrival points, and the purpose of the flights [10], and to geographical features, such as the transport accessibility of airports [11].  
Due to economic changes and their impact on air traffic in the air transport industry, a medium-term planning horizon (approximately five years) is considered the optimal horizon for estimating flight demand [12]. Medium-term forecasts provide key data for making decisions on aviation infrastructure planning, in particular, airline route network load planning [13].  
The object of the current study is the problem of medium-term forecasting of passenger demand for air transportation, which is caused by the complexity of modeling the relationships between numerous factors influencing demand. This problem covers aspects related to the development of mathematical and numerical models for assessing changes in passenger flows on a planning horizon of up to five years. The study examines the international experience in the development of passenger demand forecasting models in the air transport industry and proposes the creation of an applied solution based on an analysis of the industry's particular characteristics and existing solutions.  
This study aims to develop a model for the medium-term estimation of passenger travel demand by flight destination. The study's objectives are to ascertain the functional requirements for the model through an analysis of industry-specific details, select forecasting methods and tools, describe the model's algorithm, test the model on historical data for one flight direction, and evaluate the accuracy of the demand forecast.