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Evolutionary Approach to Constructing a Deep Feedforward Neural Network for Prediction of Electronic Coupling Elements in Molecular Materials
[Image: see text] We present a general framework for the construction of a deep feedforward neural network (FFNN) to predict distance and orientation dependent electronic coupling elements in disordered molecular materials. An evolutionary algorithm automatizes the selection of an optimal architectu...
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| Опубликовано в: : | J Chem Theory Comput |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
American
Chemical Society
2019
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| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6581422/ https://ncbi.nlm.nih.gov/pubmed/30753071 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acs.jctc.8b01285 |
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