Complex networks to differentiate elderly and young people (2021)
- Authors:
- USP affiliated authors: RODRIGUES, FRANCISCO APARECIDO - ICMC ; PINEDA, ARUANE MELLO - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-76228-5_31
- Subjects: ANÁLISE DE SÉRIES TEMPORAIS; REDES COMPLEXAS; DOENÇAS CARDIOVASCULARES; APRENDIZADO COMPUTACIONAL
- Keywords: Electrocardiogram; Statistical tests
- Language: Inglês
- Imprenta:
- Source:
- Título: Communications in Computer and Information Science
- Volume/Número/Paginação/Ano: v. 1410, p. 435-444, 2020
- Conference titles: Annual International Conference on Information Management and Big Data - SIMBig
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PINEDA, Aruane Mello e RODRIGUES, Francisco Aparecido. Complex networks to differentiate elderly and young people. Communications in Computer and Information Science. Cham: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/978-3-030-76228-5_31. Acesso em: 31 dez. 2025. , 2021 -
APA
Pineda, A. M., & Rodrigues, F. A. (2021). Complex networks to differentiate elderly and young people. Communications in Computer and Information Science. Cham: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1007/978-3-030-76228-5_31 -
NLM
Pineda AM, Rodrigues FA. Complex networks to differentiate elderly and young people [Internet]. Communications in Computer and Information Science. 2021 ; 1410 435-444.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/978-3-030-76228-5_31 -
Vancouver
Pineda AM, Rodrigues FA. Complex networks to differentiate elderly and young people [Internet]. Communications in Computer and Information Science. 2021 ; 1410 435-444.[citado 2025 dez. 31 ] Available from: https://doi.org/10.1007/978-3-030-76228-5_31 - Machine learning-based prediction of Q-voter model in complex networks
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Informações sobre o DOI: 10.1007/978-3-030-76228-5_31 (Fonte: oaDOI API)
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