Data generation and deep neural network predictions for aged mechanical properties (2025)
Source: Polymer Engineering and Science. Unidade: EESC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZAGEM PROFUNDA, POLÍMEROS (MATERIAIS), ENGENHARIA AERONÁUTICA
ABNT
PIRES, Ênio H. et al. Data generation and deep neural network predictions for aged mechanical properties. Polymer Engineering and Science, p. 1-17, 2025Tradução . . Disponível em: http://dx.doi.org/10.1002/pen.27196. Acesso em: 21 maio 2025.APA
Pires, Ê. H., Barros, S. de, Casari, P., & Ribeiro, M. L. (2025). Data generation and deep neural network predictions for aged mechanical properties. Polymer Engineering and Science, 1-17. doi:10.1002/pen.27196NLM
Pires ÊH, Barros S de, Casari P, Ribeiro ML. Data generation and deep neural network predictions for aged mechanical properties [Internet]. Polymer Engineering and Science. 2025 ; 1-17.[citado 2025 maio 21 ] Available from: http://dx.doi.org/10.1002/pen.27196Vancouver
Pires ÊH, Barros S de, Casari P, Ribeiro ML. Data generation and deep neural network predictions for aged mechanical properties [Internet]. Polymer Engineering and Science. 2025 ; 1-17.[citado 2025 maio 21 ] Available from: http://dx.doi.org/10.1002/pen.27196