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Yangqing Xu, Yuxiang Zhao, Qiangqiang Jiang, Jie Sun, Chengxin Tian and Wei Jiang
During the construction of deep foundation pits in subways, it is crucial to closely monitor the horizontal displacement of the pit enclosure to ensure stability and safety, and to reduce the risk of structural damage caused by pit deformations. With adv...
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Sunny Kumar Poguluri and Yoon Hyeok Bae
The incorporation of machine learning (ML) has yielded substantial benefits in detecting nonlinear patterns across a wide range of applications, including offshore engineering. Existing ML works, specifically supervised regression models, have not underg...
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Jessica S. Ortiz, Richard S. Pila, Joel A. Yupangui and Marco M. Rosales
The teaching?learning process developed was based on the effective integration of the Hardware in the Loop (HIL) technique to control a brewing process. This required programming the autonomous control of the system and uploading it to a physical control...
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Bohdan Petryshyn, Serhii Postupaiev, Soufiane Ben Bari and Armantas Ostreika
The development of autonomous driving models through reinforcement learning has gained significant traction. However, developing obstacle avoidance systems remains a challenge. Specifically, optimising path completion times while navigating obstacles is ...
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George Papageorgiou, Vangelis Sarlis and Christos Tjortjis
This study utilized advanced data mining and machine learning to examine player injuries in the National Basketball Association (NBA) from 2000?01 to 2022?23. By analyzing a dataset of 2296 players, including sociodemographics, injury records, and financ...
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