The Model for Forecasting Livestock Production Using FB-Prophet
Kulyk A. B., Lisovska V. P., , Shchekan N. P.

Kulyk, Anatolii B. et al. (2025) “The Model for Forecasting Livestock Production Using FB-Prophet.” The Problems of Economy 1:367–373.
https://doi.org/10.32983/2222-0712-2025-1-367-373

Section: Mathematical methods and models in economy

UDC 004.94,330.4,338.4

Abstract:
The article carries out an analysis, focusing on approaches to predicting the population of pigs in the Poltava region based on time series analysis methods. The research aims to enhance models that take into account the specific regional conditions, seasonal fluctuations, and the impact of external factors such as economic and social crises. The primary objective of the publication is to forecast the dynamics of pig population growth and to determine the optimal period for such forecasting. The Prophet model is utilized in this study, allowing for effective consideration of seasonal trends, thus ensuring high forecasting accuracy even in challenging economic conditions. The dynamics of the pig population during 2007–2024 are presented and illustrated graphically. An analysis of the statistical characteristics of the time series has been conducted, such as the mean value, standard deviation, minimum and maximum values, skewness, and kurtosis. The accuracy of the forecast has been determined and assessed using RMSE, MAE, and MAPE metrics for various forecasting horizons. The optimal forecasting period was found to be 12 months. The practical value of this study lies in the possibility of applying the obtained models for informed managerial decision-making in the field of agricultural livestock breeding. The use of such models contributes to the optimization of planning, production, storage, and sales processes, which allows for the reduction of risks associated with changes in market conditions and external threats. The developed approaches may serve as a foundation for the strategic planning of agrarian enterprises’ development, improving their economic indicators, and ensuring industry stability. The obtained results are valuable for both scientific research and practical activities in the agribusiness sector, providing support for managerial decisions at various levels – from operational planning to the development of regional development programs.

Keywords: time series, forecasting, Prophet model, livestock.

Fig.: 3. Tabl.: 3. Formulae: 4. Bibl.: 14.

Kulyk Anatolii B. – Candidate of Sciences (Physics and Mathematics), Associate Professor, Head of the Department, Department of Higher Mathematics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine)
Email: ankulyk@kneu.edu.ua
Lisovska Valentyna P. – Candidate of Sciences (Physics and Mathematics), Associate Professor, Professor, Department of Higher Mathematics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine)
Email: lisovska@kneu.edu.ua
–
Shchekan Nadiia P. – Senior Lecturer, Department of Higher Mathematics, Kyiv National Economic University named after Vadym Hetman (54/1 Beresteiskyi Ave., Kyiv, 03057, Ukraine)
Email: shchekan.nadiia@kneu.edu.ua

List of references in article

Holovne upravlinnia statystyky v Poltavskii oblasti. https://www.pl.ukrstat.gov.ua/
Khatib, A. M. G. et al. “Modeling and forecasting of egg production in India using time series models“. Eurasian J Vet Sci., vol. 37 (4) (2021): 265-273. DOI: https://doi.org/10.15312/EurasianJVetSci.2021.352
Bina, V., Bartosova, J., and Pribyl, V. “Anomaly detection in time series for smart agriculture“. International Journal of Management, Knowledge and Learning, vol. 11 (2022). DOI: https://doi.org/10.53615/2232-5697.11.177-186
Chadalavada, R., Raghavendra, S., and Rekha, V. “Electricity requirement prediction using time series and Facebook's PROPHET“. Indian Journal of Science and Technology, vol. 13 (47) (2020): 4631-4645. DOI: https://doi.org/10.17485/IJST/v13i47.1847
Hasnain, A. et al. “Time series analysis and forecasting of air pollutants based on prophet forecasting model in Jiangsu province, China“. Frontiers in Environmental Science, vol. 10. 945628 (2022). DOI: https://doi.org/10.3389/fenvs.2022.945628
Henchion, M. et al. “Review: Trends for meat, milk and egg consumption for the next decades and the role played by livestock systems in the global production of proteins“. Animal, vol. 15 (1). 100287 (2021). DOI: https://doi.org/10.1016/j.animal.2021.100287
Jha, B. K., and Pande, S. “Time series forecasting model for supermarket sales using FB-prophet“. 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. 547-554. DOI: https://doi.org/10.1109/ICCMC51019.2021.9418033
Kanthi, S. S., and Vallabaneni, S. “Entrepreneur Development Through Pig Farming“. In Good Practices and Principles in Pig Farming. Livestock Diseases and Management. Singapore: Springer, 2024. DOI: https://doi.org/10.1007/978-981-97-4665-1_12
Kassenbayev, G. et al. “Animal husbandry market in Kazakhstan: Dynamics and prognosis“. Scientific Horizons, vol. 27 (4) (2024): 176-188. DOI: https://doi.org/10.48077/scihor4.2024.176
Klaharn, K. et al. “Analyzing and forecasting poultry meat production and export volumes in Thailand: a time series approach“. Cogent Food & Agriculture, vol. 10 (1) (2024). DOI: https://doi.org/10.1080/23311932.2024.2378173
Omar, M. A. et al. “The usage of the autoregressive integrated moving average model for forecasting milk production in Egypt (2022-2025)“. Open Veterinary Journal, vol. 14 (1) (2024): 256-265. DOI: https://doi.org/10.5455/OVJ.2024.v14.i1.22
Saiktishna, C. et al. “Historical analysis and time series forecasting of stock market using FB prophet“. 6th International conference on intelligent computing and control systems (ICICCS). IEEE, 2022. 1846-1851. DOI: https://doi.org/10.1109/ICICCS53718.2022.9788231
Sharma, K., Bhalla, R., and Ganesan, G. “Time series forecasting using FB-Prophet“. Algorithms Computing and Mathematics Conference (ACM-2022). Chennai, India, 2022. https://ceur-ws.org/Vol-3445/PAPER_07.pdf
Zakhodym, V. “Methodology of modeling trends of livestock products market development“. Podilian Bulletin: agriculture, engineering, economics, vol. 38 (1) (2023): 125-131. DOI: https://doi.org/10.37406/2706-9052-2023-1.18