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Publikováno v:
The Journal of the Acoustical Society of America. 151:A253-A253
Traditional approaches to numerically model acoustic metasurfaces (AMS) with deeply subwavelength features require tremendous computational expense. Metamodels created using machine learning (ML) methods are promising techniques to efficiently and ac