ASAMS: An Adaptive Sequential Sampling and Automatic Model Selection for Artificial Intelligence Surrogate Modeling

Surrogate Modeling (SM) is often used to reduce the computational burden of time-consuming system simulations. However, continuous advances in Artificial Intelligence (AI) and the spread of embedded sensors have led to the creation of Digital Twins (DT), Design Mining (DM), and Soft Sensors (SS). Th...

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Detalles Bibliográficos
Autores principales: Duchanoy, Carlos A., Calvo, Hiram, Moreno-Armendáriz, Marco A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571090/
https://www.ncbi.nlm.nih.gov/pubmed/32957671
http://dx.doi.org/10.3390/s20185332

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571090/
https://www.ncbi.nlm.nih.gov/pubmed/32957671
http://dx.doi.org/10.3390/s20185332

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