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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...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| 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 |