A Modeling Framework of Dynamic Risk Monitoring for Chemical Processes Based on Complex Networks

A Modeling Framework of Dynamic Risk Monitoring for Chemical Processes Based on Complex Networks

To ensure the stable and safe operations, this paper presents a modeling framework of dynamic risk monitoring for chemical processes. Multi-source process data are firstly denoised by the Wavelet Transform (WT). The Spearman’s rank correlation coefficient (SRCC) of these data is calculate...

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Bibliographic Details
Main Authors: Qianlin Wang, Jiaqi Han, Feng Chen, Feng Wang, Zhan Dou, Guoan Yang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Chemical process
risk monitoring
complex network (CN)
Spearman’s rank correlation coefficient (SRCC)
network structure entropy
Online Access:https://ieeexplore.ieee.org/document/10403879/

Internet

https://ieeexplore.ieee.org/document/10403879/

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