Demand Forecasting Model for Airline Flights Based on Historical Passenger Flow Data
Source abstract
Abstract
This paper addresses the problem of estimating passenger demand for flights, with a particular focus on the necessity of developing precise forecasts that incorporate intricate and interdependent variables for effective resource planning within the air transport industry. The present paper focuses on the development of a model for medium-term flight demand estimation by flight destinations. This is based on the analysis of historical airline data on dates, departure times, and passenger demand, as well as the consideration of the influence of macroeconomic indicators, namely gross regional product (GRP), median per capita income, and population of departure and arrival points. This paper reviews international experience in the development of demand forecasting models and their use for resource planning in the industry. The developed model was evaluated using historical data on demand for a single turnaround flight operated by an airline. The developed model allows for the forecasting of the distribution of potential demand for airline flight destinations in the medium term, utilizing comprehensive historical data on departure times and flight demand by destination.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Aviation Industry Analysis and Trends · Air Traffic Management and Optimization · Transportation Planning and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Laboratory “Digital Modelling of Industrial Systems”, Advanced Engineering School “Digital Engineering”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
Laboratory “Industrial Streaming Data Processing Systems”, Advanced Engineering School “Digital Engineering”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
Funding
Ministry of Science and Higher Education of the Russian Federation
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