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NTIS 바로가기지구물리와 물리탐사 = Geophysics and geophysical exploration, v.26 no.3, 2023년, pp.114 - 125
조상인 (인하대학교 에너지자원공학과) , 최우창 (인하대학교 에너지자원공학과) , 지준 (한성대학교 AI응용학과) , 편석준 (인하대학교 에너지자원공학과)
The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function,...
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