Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Hussein, I.A. and Muhsan, A.S. and Ridha, S. and Salih, A.A. (2024) A gated recurrent unit model to predict Poisson's ratio using deep learning. Journal of Rock Mechanics and Geotechnical Engineering, 16 (1). pp. 123-135.

Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Muhsan, A.S. and Abdulkadir, S.J. and Hussein, I.A. and Salih, A.A. (2023) Prediction of critical total drawdown in sand production from gas wells: Machine learning approach. Canadian Journal of Chemical Engineering, 101 (5). pp. 2493-2509.

Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Muhsan, A.S. and Hussein, I.A. (2023) A robust Gaussian process regression-based model for the determination of static Young�s modulus for sandstone rocks. Neural Computing and Applications, 35 (21). pp. 15693-15707.

Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Muhsan, A.S. and Hussein, I.A. (2022) An Accurate Reservoir's Bubble Point Pressure Correlation. ACS Omega, 7 (15). pp. 13196-13209. ISSN 24701343

Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Muhsan, A.S. and Hussein, I.A. (2022) A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis. PLoS ONE, 17 (8 Augu). ISSN 19326203

Alakbari, F.S. and Mohyaldinn, M.E. and Ayoub, M.A. and Muhsan, A.S. and Hussein, I.A. (2021) A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells. PLoS ONE, 16 (4 Apri). ISSN 19326203