Cargando…
Pseudo-Labeling Optimization Based Ensemble Semi-Supervised Soft Sensor in the Process Industry
Nowadays, soft sensor techniques have become promising solutions for enabling real-time estimation of difficult-to-measure quality variables in industrial processes. However, labeled data are often scarce in many real-world applications, which poses a significant challenge when building accurate sof...
Autores principales: | Li, Youwei, Jin, Huaiping, Dong, Shoulong, Yang, Biao, Chen, Xiangguang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8708742/ https://www.ncbi.nlm.nih.gov/pubmed/34960564 http://dx.doi.org/10.3390/s21248471 |
Ejemplares similares
-
Online-Dynamic-Clustering-Based Soft Sensor for Industrial Semi-Supervised Data Streams
por: Wang, Yuechen, et al.
Publicado: (2023) -
Deep Semi-Supervised Just-in-Time Learning Based Soft Sensor for Mooney Viscosity Estimation in Industrial Rubber Mixing Process
por: Zhang, Yan, et al.
Publicado: (2022) -
Semi-supervised multi-label collective classification ensemble for functional genomics
por: Wu, Qingyao, et al.
Publicado: (2014) -
A Semi-Supervised Stacked Autoencoder Using the Pseudo Label for Classification Tasks
por: Lai, Jie, et al.
Publicado: (2023) -
Medical Image Classification Based on Semi-Supervised Generative Adversarial Network and Pseudo-Labelling
por: Liu, Kun, et al.
Publicado: (2022)