مدل‌سازی‌ متغیرهای‌ موثر ‌بر ‌عملکرد مزارع ‌نیشکر با استفاده از شبکه عصبی بازگشتی عمیق

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Ed-Daoudi, R., Alaoui, A., Ettaki, B., & Zerouaoui, J. (2023). Improving Crop Yield Predictions in Morocco Using Machine Learning Algorithms. Journal of Ecological Engineering, 24(6)‏: 392-400. https://doi.org/10.12911/22998993/162769

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Sattari, M. T., shirini, K., & javidan, S. (2024). Evaluating the efficiency of dimensionality reduction methods in improving the accuracy of water quality index modeling in Qizil-Uzen River using machine learning algorithms. Water and Soil Management and Modelling, 4(2), 89-104. doi: 10.22098/mmws.2023.12434.1241. (in Persian).

Shirini, K., Kordan, M.B. & Gharehveran, S.S. (2025) Impact of learning rate and epochs on LSTM model performance: a study of chlorophyll-a concentrations in the Marmara Sea. Journal of Supercomputing, 81, 265. https://doi.org/10.1007/s11227-024-06806-2

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Zaki Dizaji, H., Monjezi, N., & Sheikhdavoodi, J. (2018). Investigating Effective Factors on Sugarcane Production Performance to Increase the Production of Sugarcane Using Data Mining. Iranian Journal of Biosystems Engineering, 49(3), 501-511. doi: 10.22059/ijbse.2018.248601.665021. (in Persian).

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