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Ebenezer O. Oluwasakin and Abdul Q. M. Khaliq
Artificial neural networks have changed many fields by giving scientists a strong way to model complex phenomena. They are also becoming increasingly useful for solving various difficult scientific problems. Still, people keep trying to find faster and m...
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Abdulrazak Jinadu Otaru, Olalekan David Adeniyi, Ige Bori, Olufemi Ayodeji Olugboji and Joseph Obofoni Odigure
In recent decades, cellular metallic materials have increasingly been used for control of reverberation and cutback. These materials offer a unique combination of expanded pores, high specific surfaces, improved structural performance, low weight, corros...
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Celal Cakiroglu
The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (...
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Charalampos Papakonstantinou, Ioannis Daramouskas, Vaios Lappas, Vassilis C. Moulianitis and Vassilis Kostopoulos
This paper addresses the problem of singularity avoidance for a 4-Control Moment Gyroscope (CMG) pyramid cluster, as used for the attitude control of a satellite using machine learning (ML) techniques. A data-set, generated using a heuristic algorithm, r...
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Cheng Zeng, Yimo Bai, Jie Zhou, Fei Qiu, Shaowei Ding, Yudie Hu and Lingling Wang
Floodplain vegetation is of great importance in velocity distribution and turbulent coherent structure within compound open channel flows. As the large eddy simulation (LES) technique can provide detailed instantaneous flow dynamics and coherent turbulen...
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