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Year 2023, Volume: 23, 531 - 538, 30.09.2023
https://doi.org/10.55549/epstem.1374922

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.

Estimation of Poultry Meat Production in Turkey Using GM (1,1) with Second Parameter Fitting-Markov Model

Year 2023, Volume: 23, 531 - 538, 30.09.2023
https://doi.org/10.55549/epstem.1374922

Abstract

Considering that poultry meat is an economical and stable food source and its place in a balanced diet, it is an indispensable food item for today as well as tomorrow. It is the most produced poultry meat in the world among other meat types since 2015. Turkey ranks 10th in the world in chicken meat production. Chicken farming and backyard poultry farming, which was mostly family-run until the 1980s, has left its place to giant facilities today. There are over 15,000 broiler breeding farms in Turkey and the annual turnover of the sector, which provides a livelihood for approximately 3 million people with all its stakeholders, has reached 5.5 billion USD. It is currently the biggest alternative to red meat. Today, white meat is preferred all over the world in terms of protein source and the per capita consumption of poultry meat is increasing every year in the world. Our per capita consumption of poultry meat has reached 21 kg/year. Accurate estimation of poultry meat production in Turkey is important for establishing short, medium and long-term policies that will balance supply and demand. In this study, GM (1, 1) with second parameter fitting-Markov model, which is a combination of the Markov chain method and the GM (1, 1) model with the second parameter fitting, which can be used to predict future data with very limited data and information, was used in the estimation of poultry meat production. The obtained results show that GM (1, 1) with second parameter fitting-Markov 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.
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Details

Primary Language English
Subjects Environmental and Sustainable Processes
Journal Section Articles
Authors

Halil Sen

Early Pub Date October 12, 2023
Publication Date September 30, 2023
Published in Issue Year 2023Volume: 23

Cite

APA Sen, H. (2023). Estimation of Poultry Meat Production in Turkey Using GM (1,1) with Second Parameter Fitting-Markov Model. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 531-538. https://doi.org/10.55549/epstem.1374922