| Title: | N-Beats architecture for explainable forecasting of multi-dimensional poultry data |
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| Authors: | ID Kaur, Baljinder (Author)
ID Rakhra, Manik (Author)
ID Sharma, Nonita (Author)
ID Prashar, Deepak (Author)
ID Mršić, Leo (Author)
ID Khan, Arfat Ahmad (Author)
ID Kadry, Seifedine (Author) |
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| Files: |  URL - Source URL, visit https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0320979
 PDF - Presentation file, download (1,63 MB)
MD5: A6246FB7FE3238E1B645229D9D6799B3
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  RUDOLFOVO - Rudolfovo - Science and Technology Centre Novo Mesto
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| Abstract: | The agricultural economy heavily relies on poultry production, making accurate forecasting of poultry data crucial for optimizing revenue, streamlining resource utilization, and maximizing productivity. This research introduces a novel application of the N-BEATS architecture for multi-dimensional poultry data forecasting with enhanced interpretability through an integrated Explainable AI (XAI) framework. Leveraging its advanced capabilities in time series modeling, N-BEATS is applied to predict multiple facets of poultry disease diagnostics using a multivariate dataset comprising key environmental parameters. The methodology empowers decision-making in poultry farm management by providing transparent and interpretable forecasts. Experimental results demonstrate that N-BEATS outperforms conventional deep learning models, including LSTM, GRU, RNN, and CNN, across various error metrics, achieving MAE of 0.172, RMSE of 0.313, MSLE of 0.042, R-squared of 0.034, and RMSLE of 0.204. The positive R-squared value indicates the model’s robustness against underfitting and overfitting, surpassing the performance of other models with negative R-squared values. This study establishes N-BEATS as a superior and interpretable solution for complex, multi-dimensional forecasting challenges in poultry production, with significant implications for enhancing predictive analytics in agriculture. |
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| Keywords: | poultry, livestock, forecasting, epidemiology, humidity, veterinary diseases, polynomials |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 24.04.2025 |
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| Publisher: | Public Library of Science |
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| Year of publishing: | 2025 |
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| Number of pages: | str. 1-19 |
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| Numbering: | Vol. 20, iss. 4 |
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| PID: | 20.500.12556/DiRROS-22649  |
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| UDC: | 519.87:004.92:636.52 |
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| ISSN on article: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0320979 |
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| COBISS.SI-ID: | 239347459 |
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| Copyright: | © 2025 Kaur et al. |
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| Note: | Soavtorji: Manik Rakhra, Nonita Sharma, Deepak Prashar, Leo Mrsic, Arfat Ahmad Khan, Seifedine Kadry;
Nasl. z nasl. zaslona;
Opis vira z dne 13. 6. 2024;
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| Publication date in DiRROS: | 09.09.2025 |
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| Views: | 270 |
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| Downloads: | 109 |
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