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

Transport 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.