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Year 2023, Volume: 23, 179 - 188, 30.09.2023
https://doi.org/10.55549/epstem.1365776

Abstract

References

  • Chen, L. H., & Guo, T. Y. (2011). Forecasting financial crises for an enterprise by using the Grey Markov forecasting model. Quality and Quantity, 45(4), 911–922.
  • Dong, S., Chi, K., Zhang, Q., & Zhang, X. (2012). The application of a Grey Markov model to forecasting annual maximum water levels at hydrological stations. Journal of Ocean University of China, 11(1), 13–17.
  • Duan, J., Jiao, F., Zhang, Q., & Lin, Z. (2017). Predicting urban medical services demand in China: an improved Grey Markov Chain model by Taylor approximation. International Journal of Environmental Research and Public Health, 14(8), 883.
  • Ertas, N. (2023). Uretim, tuketim ve pazarlama yonleriyle gecmisten gunumuze dunya kırmızı et piyasasında Turkiye’nin yeri. Academic Social Resources Journal, 8(46), 2191–2214.

Estimation of Red Meat Production in Turkey according to the Grey-Markov Chain Model

Year 2023, Volume: 23, 179 - 188, 30.09.2023
https://doi.org/10.55549/epstem.1365776

Abstract

Today, due to the place and importance of red meat in terms of nutrition and public health, meeting the reliable supply of red meat to meet the demand has become one of the most important issues. The production source of red meat in Turkey is cattle, sheep, goat and buffalo. Although Turkey is a rich country in terms of different species and breeds and animal potential, the yield per unit animal is low. Most of the meat is consumed fresh in Turkey. With the increasing importance of meeting the reliable red meat supply, the necessity of following the sector has emerged. Accurate estimation of red meat production in Turkey is important for establishing short, medium and long-term policies that will balance supply and demand. In this study, Grey-Markov chain model, which is a combination of Markov chains method and Grey estimation model, which can be used to predict future data with very limited data and information, was used in the estimation of red meat production. The obtained results show that the Grey-Markov chain model used has high predictive precision and applicability.

References

  • Chen, L. H., & Guo, T. Y. (2011). Forecasting financial crises for an enterprise by using the Grey Markov forecasting model. Quality and Quantity, 45(4), 911–922.
  • Dong, S., Chi, K., Zhang, Q., & Zhang, X. (2012). The application of a Grey Markov model to forecasting annual maximum water levels at hydrological stations. Journal of Ocean University of China, 11(1), 13–17.
  • Duan, J., Jiao, F., Zhang, Q., & Lin, Z. (2017). Predicting urban medical services demand in China: an improved Grey Markov Chain model by Taylor approximation. International Journal of Environmental Research and Public Health, 14(8), 883.
  • Ertas, N. (2023). Uretim, tuketim ve pazarlama yonleriyle gecmisten gunumuze dunya kırmızı et piyasasında Turkiye’nin yeri. Academic Social Resources Journal, 8(46), 2191–2214.
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Details

Primary Language English
Subjects Food Engineering
Journal Section Articles
Authors

Halil Sen

Early Pub Date September 25, 2023
Publication Date September 30, 2023
Published in Issue Year 2023Volume: 23

Cite

APA Sen, H. (2023). Estimation of Red Meat Production in Turkey according to the Grey-Markov Chain Model. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 179-188. https://doi.org/10.55549/epstem.1365776