Forecasting the Tobacco Market in Türkiye with Artificial Neural Networks

Authors : Aysel Topşir, Ferdi Güler

Pages : 688-701

Doi:10.31466/kfbd.1570632

View : 73 | Download : 44

Publication Date : 2025-06-15

Article Type : Research Paper

Abstract :This study aims to forecast the future dynamics of tobacco policies in Türkiye using artificial neural networks. Tobacco production, area harvested, and yield data from 1961 to 2022 were comprehensively analyzed to understand the complex relationships among these variables. The results indicate that, while tobacco production and harvested area are expected to decline gradually between 2023 and 2027, yield will significantly increase. This trend reflects the positive impact of technological advancements and effective agricultural policies. Time series forecasting was conducted using DeepDenT software. These forecasts provide valuable insights for the sustainability and strategic planning of tobacco farming. In addition to forecasting, the study applied the linear Granger causality test to assess relationships between the variables. However, no statistically significant causality was found, suggesting that tobacco production is influenced by complex, non-linear dynamics. This implies that conventional linear models may be insufficient to capture the true nature of the production process. Overall, the study offers critical insights into long-term trends in tobacco agriculture and contributes to policy development. It supports producers in making informed, strategic decisions and enhances understanding of the sector’s sustainability and economic stability. Thus, the study offers a new perspective on optimizing production through data-driven approaches and advanced modeling.
Keywords : Öngörü, Tütün Analizi, Yapay Sinir Ağları

ORIGINAL ARTICLE URL