Evaluation of Machine Learning and Traditional Methods for Estimating Compressive Strength of UHPC von Li, Tianlong, Jiang, Pengxiao, Qian, Yunfeng, Yang, Jianyu, AlAteah, Ali H., Alsubeai, Ali, Alfares, Abdulgafor M., Sufian, Muhammad

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Predicting High-Strength Concrete's Compressive Strength: A Comparative Study of Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, and Response Surface Methodology von Li, Tianlong, Yang, Jianyu, Jiang, Pengxiao, AlAteah, Ali H, Alsubeai, Ali, Alfares, Abdulgafor M, Sufian, Muhammad

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Prediction of Ultra-High-Performance Concrete (UHPC) Properties Using Gene Expression Programming (GEP) von Qian, Yunfeng, Yang, Jianyu, Yang, Weijun, Alateah, Ali H., Alsubeai, Ali, Alfares, Abdulgafor M., Sufian, Muhammad

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CVD based synthesis of binder free nanostructured MgS/MoS2@NiF electrode material for asymmetric supercapacitor applications von Raza, A., Farid, A., Yousaf, Misbah, Alfares, Abdulgafor M., Rasheed, A., Khan, I.A., Ghanem, Mohamed A., Mohammed, Khaled M.H.

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Synthesis and electrochemical properties of microcanals Mg-S-Cu-S as an electrode material for energy storage applications von Ahsan Ali, M., Farid, A., Rasheed, A., Yousaf, Misbah, Alfares, Abdulgafor M., Ayub, N., Khan, I.A., Ghanem, Mohamed A., Marken, Frank

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Prediction of Ultra-High-Performance Concrete von Qian, Yunfeng, Yang, Jianyu, Yang, Weijun, Alateah, Ali H, Alsubeai, Ali, Alfares, Abdulgafor M, Sufian, Muhammad

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