Permeability Prediction of Nanoscale Porous Materials Using Discrete Cosine Transform-Based Artificial Neural Networks

The permeability of porous materials determines the fluid flow rate and aids in the prediction of their mechanical properties. This study developed a novel approach that combines the discrete cosine transform (DCT) and artificial neural networks (ANN) for permeability analysis and prediction in digi...

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Detalles Bibliográficos
Autores principales: Li, Dongshuang, You, Shaohua, Liao, Qinzhuo, Lei, Gang, Liu, Xu, Chen, Weiqing, Li, Huijian, Liu, Bo, Guo, Xiaoxi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342421/
https://www.ncbi.nlm.nih.gov/pubmed/37444982
http://dx.doi.org/10.3390/ma16134668

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342421/
https://www.ncbi.nlm.nih.gov/pubmed/37444982
http://dx.doi.org/10.3390/ma16134668

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