Energy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application

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dc.authoridDOGAN, Erdem/0000-0001-7802-641X
dc.authoridKORKMAZ, Ersin/0000-0003-3725-164X
dc.contributor.authorKorkmaz, Ersin
dc.contributor.authorDogan, Erdem
dc.contributor.authorAkgungor, Ali Payidar
dc.date.accessioned2025-01-21T16:38:34Z
dc.date.available2025-01-21T16:38:34Z
dc.date.issued2024
dc.departmentKırıkkale Üniversitesi
dc.description.abstractTransport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey's energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements.
dc.identifier.doi10.3390/en17194979
dc.identifier.issn1996-1073
dc.identifier.issue19
dc.identifier.scopus2-s2.0-85206498021
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/en17194979
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24692
dc.identifier.volume17
dc.identifier.wosWOS:001332224900001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofEnergies
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjecttransportation energy demand; Walrus Optimization algorithm; White Shark Optimizer algorithm; future projections
dc.titleEnergy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application
dc.typeArticle

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