The Application of Machine Learning in Geotechnical Engineering
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The purpose of the following reprint is to update readers on the latest applications of machine learning methods in the field of geotechnical engineering, from planning and design to construction. Because the objects of geotechnical engineering are natural geological bodies, whose mechanical properties and internal structure are very complex, most geotechnical engineering problems involve the coupling of multiple fields and multiple phases. Therefore, traditional methods (e.g., theoretical methods, numerical methods, and experimental methods) cannot solve geotechnical engineering problems well...
The purpose of the following reprint is to update readers on the latest applications of machine learning methods in the field of geotechnical engineering, from planning and design to construction. Because the objects of geotechnical engineering are natural geological bodies, whose mechanical properties and internal structure are very complex, most geotechnical engineering problems involve the coupling of multiple fields and multiple phases. Therefore, traditional methods (e.g., theoretical methods, numerical methods, and experimental methods) cannot solve geotechnical engineering problems well. The development of artificial intelligence has supported better solutions to geotechnical engineering problems, and machine learning methods have been applied widely, currently representing a hot research topic. As a part of this reprint, leading experts in the field share their insights, research findings, and visions for the future. Together, we embark on a journey to unlock the full potential of machine learning method applications in the field of geotechnical engineering.
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