Time series prediction via similarity search: exploring invariances, distance measures and ensemble functions (2022)
- Authors:
- Autor USP: PARMEZAN, ANTONIO RAFAEL SABINO - ICMC
- Unidade: ICMC
- DOI: 10.1109/ACCESS.2022.3192849
- Subjects: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS); RECONHECIMENTO DE PADRÕES
- Keywords: Forecasting; multi-step-ahead prediction; pattern sequence similarity; univariate analysis
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway
- Date published: 2022
- Source:
- Título do periódico: IEEE Access
- ISSN: 2169-3536
- Volume/Número/Paginação/Ano: v. 10, p. 78022-78043, 2022
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
ABNT
PARMEZAN, Antonio Rafael Sabino e SOUZA, Vinícius Mourão Alves de e BATISTA, Gustavo Enrique de Almeida Prado Alves. Time series prediction via similarity search: exploring invariances, distance measures and ensemble functions. IEEE Access, v. 10, p. 78022-78043, 2022Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2022.3192849. Acesso em: 05 jun. 2024. -
APA
Parmezan, A. R. S., Souza, V. M. A. de, & Batista, G. E. de A. P. A. (2022). Time series prediction via similarity search: exploring invariances, distance measures and ensemble functions. IEEE Access, 10, 78022-78043. doi:10.1109/ACCESS.2022.3192849 -
NLM
Parmezan ARS, Souza VMA de, Batista GE de APA. Time series prediction via similarity search: exploring invariances, distance measures and ensemble functions [Internet]. IEEE Access. 2022 ; 10 78022-78043.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1109/ACCESS.2022.3192849 -
Vancouver
Parmezan ARS, Souza VMA de, Batista GE de APA. Time series prediction via similarity search: exploring invariances, distance measures and ensemble functions [Internet]. IEEE Access. 2022 ; 10 78022-78043.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1109/ACCESS.2022.3192849 - Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets
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Informações sobre o DOI: 10.1109/ACCESS.2022.3192849 (Fonte: oaDOI API)
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