Online anomaly explanation: a case study on predictive maintenance (2023)
- Authors:
- Autor USP: MASTELINI, SAULO MARTIELLO - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-031-23633-4_25
- Subjects: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS); APRENDIZAGEM PROFUNDA
- Keywords: Explainable AI; Rare events; Predictive maintenance
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Communications in Computer and Information Science
- ISSN: 1865-0929
- Volume/Número/Paginação/Ano: v. 1753, p. 383-399, 2023
- Conference titles: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML PKDD
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
RIBEIRO, Rita P et al. Online anomaly explanation: a case study on predictive maintenance. Communications in Computer and Information Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-23633-4_25. Acesso em: 25 dez. 2025. , 2023 -
APA
Ribeiro, R. P., Mastelini, S. M., Davari, N., Aminian, E., Veloso, B. M. D., & Gama, J. (2023). Online anomaly explanation: a case study on predictive maintenance. Communications in Computer and Information Science. Cham: Springer. doi:10.1007/978-3-031-23633-4_25 -
NLM
Ribeiro RP, Mastelini SM, Davari N, Aminian E, Veloso BMD, Gama J. Online anomaly explanation: a case study on predictive maintenance [Internet]. Communications in Computer and Information Science. 2023 ; 1753 383-399.[citado 2025 dez. 25 ] Available from: https://doi.org/10.1007/978-3-031-23633-4_25 -
Vancouver
Ribeiro RP, Mastelini SM, Davari N, Aminian E, Veloso BMD, Gama J. Online anomaly explanation: a case study on predictive maintenance [Internet]. Communications in Computer and Information Science. 2023 ; 1753 383-399.[citado 2025 dez. 25 ] Available from: https://doi.org/10.1007/978-3-031-23633-4_25 - Improved prediction of soil properties with multi-target stacked generalisation on EDXRF spectra
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Informações sobre o DOI: 10.1007/978-3-031-23633-4_25 (Fonte: oaDOI API)
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