A Novel Method for Modeling and Predicting Transportation Data Via Multideep Assessment Methodology and Fractional Calculus

Autor: Şimşek Kevser, Tuğrul Nisa Özge Önal, Çam İlhan, Karaçuha Kamil, Tabatadze Vasıl, Karaçuha Ertuğrul
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Transport and Telecommunication, Vol 25, Iss 2, Pp 136-149 (2024)
Druh dokumentu: article
ISSN: 1407-6179
DOI: 10.2478/ttj-2024-0010
Popis: Aviation is one of the most global industries, and if we can model and predict a country’s air transportation flow and indicators ahead of time, we may be able to use it as a key decision-making tool for the management and operation process. This study proposes a new modeling, and prediction method that employs both fractional calculus and Multi Deep Assessment Methodology (MDAM) techniques. For the application, air passengers carried, air freight, available seat kilometers, number of flights, destination points, international travelers, international destination points, and international flight data between 2011 and 2019 for eight countries with the busiest airports were chosen. As a result, the highest modeling error was discovered to be Germany’s air transport freight factor expressed as a percentage of 1,59E-02. The percentage of predictions with errors less than 10% was 90.278. We also compared the performance of two different MDAM methodologies. The novel MDAM wd methodology proposed in this paper has a higher accuracy in aviation factors prediction and modeling.
Databáze: Directory of Open Access Journals