Cargando…
Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks
In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and da...
Autores principales: | Zhao, Rui, Yan, Ruqiang, Wang, Jinjiang, Mao, Kezhi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5336098/ https://www.ncbi.nlm.nih.gov/pubmed/28146106 http://dx.doi.org/10.3390/s17020273 |
Ejemplares similares
-
High Precision Dimensional Measurement with Convolutional Neural Network and Bi-Directional Long Short-Term Memory (LSTM)
por: Wang, Yuhao, et al.
Publicado: (2019) -
A Convolutional Neural Network Face Recognition Method Based on BiLSTM and Attention Mechanism
por: Qi, Xiaobo, et al.
Publicado: (2023) -
An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection
por: Toma, Tabassum Islam, et al.
Publicado: (2023) -
Deep Bi-LSTM Networks for Sequential Recommendation
por: Zhao, Chuanchuan, et al.
Publicado: (2020) -
Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM
por: Shahid, Farah, et al.
Publicado: (2020)