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Predicting the Dispersion Relations of One-Dimensional Phononic Crystals by Neural Networks
In this paper, deep back propagation neural networks (DBP-NNs) and radial basis function neural networks (RBF-NNs) are employed to predict the dispersion relations (DRs) of one-dimensional (1D) phononic crystals (PCs). The data sets generated by transfer matrix method (TMM) are used to train the NNs...
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| Pubblicato in: | Sci Rep |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6814748/ https://ncbi.nlm.nih.gov/pubmed/31653907 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-51662-3 |
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