Cargando…
Deep Auto-Encoder and Deep Forest-Assisted Failure Prognosis for Dynamic Predictive Maintenance Scheduling
Prognostics and health management (PHM) with failure prognosis and maintenance decision-making as the core is an advanced technology to improve the safety, reliability, and operational economy of engineering systems. However, studies of failure prognosis and maintenance decision-making have been con...
Autores principales: | Yu, Hui, Chen, Chuang, Lu, Ningyun, Wang, Cunsong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8706898/ https://www.ncbi.nlm.nih.gov/pubmed/34960474 http://dx.doi.org/10.3390/s21248373 |
Ejemplares similares
-
An AVMD-DBN-ELM Model for Bearing Fault Diagnosis
por: Lei, Xue, et al.
Publicado: (2022) -
Road-Type Classification with Deep AutoEncoder
por: Molefe, Mohale E., et al.
Publicado: (2023) -
A deep auto-encoder model for gene expression prediction
por: Xie, Rui, et al.
Publicado: (2017) -
Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection
por: Balasubramanian, Saravana Balaji, et al.
Publicado: (2022) -
Speech Enhancement Based on Deep AutoEncoder for Remote Arabic Speech Recognition
por: Dendani, Bilal, et al.
Publicado: (2020)