Batch Process Monitoring with Dynamic-Static Joint Indicator Based on GSFA-GNPE
Traditional process monitoring methods ignore the time-series correlation between variables, and do not distinguish the dynamic relationship and static relationship between variables, resulting in poor monitoring effect. To solve these problems, a dynamic-static joint indicator monitoring method of...
Guardado en:
Autor principal: | ZHAO Xiaoqiang, MOU Miao |
---|---|
Formato: | article |
Lenguaje: | ZH |
Publicado: |
Editorial Office of Journal of Shanghai Jiao Tong University
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/173bdc88199f40ecafad7c6c5c7aefc5 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Markov Chain Neighborhood Sparse Preserving Graph Embedding Based on Tensor Factorization for Batch Process Monitoring
por: Xiaoqiang Zhao, et al.
Publicado: (2021) -
Full-scale self-propulsion simulation with a discretized propeller
por: Zhang Qingshan, et al.
Publicado: (2021) -
Unsteady force measurements on propeller model in cavitation tunnels
por: Igor A. Solovyev, et al.
Publicado: (2021) -
Polish Maritime Research
Publicado: (2008) -
Validating propulsion system optimization procedure for a carrier vessel
por: Lobachev Mikhail P., et al.
Publicado: (2021)