Machine learning-based prediction of Q-voter model in complex networks (2023)
- Authors:
- USP affiliated authors: RODRIGUES, FRANCISCO APARECIDO - ICMC ; PINEDA, ARUANE MELLO - ICMC
- Unidade: ICMC
- DOI: 10.1088/1742-5468/ad06a6
- Subjects: APRENDIZADO COMPUTACIONAL; COMUNICAÇÃO; REDES DE INFORMAÇÃO
- Keywords: network dynamics; supply and information networks
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Statistical Mechanics
- ISSN: 1742-5468
- Volume/Número/Paginação/Ano: v. 2023, p. 1-33, 2023
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: hybrid
- Licença: cc-by
-
ABNT
PINEDA, Aruane Mello et al. Machine learning-based prediction of Q-voter model in complex networks. Journal of Statistical Mechanics, v. 2023, p. 1-33, 2023Tradução . . Disponível em: https://doi.org/10.1088/1742-5468/ad06a6. Acesso em: 30 abr. 2024. -
APA
Pineda, A. M., Kent, P., Connaughton, C., & Rodrigues, F. A. (2023). Machine learning-based prediction of Q-voter model in complex networks. Journal of Statistical Mechanics, 2023, 1-33. doi:10.1088/1742-5468/ad06a6 -
NLM
Pineda AM, Kent P, Connaughton C, Rodrigues FA. Machine learning-based prediction of Q-voter model in complex networks [Internet]. Journal of Statistical Mechanics. 2023 ; 2023 1-33.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1088/1742-5468/ad06a6 -
Vancouver
Pineda AM, Kent P, Connaughton C, Rodrigues FA. Machine learning-based prediction of Q-voter model in complex networks [Internet]. Journal of Statistical Mechanics. 2023 ; 2023 1-33.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1088/1742-5468/ad06a6 - Complex networks to differentiate elderly and young people
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Informações sobre o DOI: 10.1088/1742-5468/ad06a6 (Fonte: oaDOI API)
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