Real-Time Event-Driven Learning in Highly Volatile Systems: A Case for Embedded Machine Learning for SCADA Systems

Real-Time Event-Driven Learning in Highly Volatile Systems: A Case for Embedded Machine Learning for SCADA Systems

Extracting key system parameters and their impact on state transition is a necessity for knowledge and data engineering. In Decision Support Systems, the quest for yet more efficient and faster methods of sensitivity analysis (SA) and feature extraction in complex and volatile systems persists. A ne...

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Bibliographic Details
Main Authors: Manuel Goncalves, Pedro Sousa, Jerome Mendes, Morad Danishvar, Alireza Mousavi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Event Tracking
sensitivity analysis (SA)
discrete event systems
input variable selection
real-time systems
distributed computing
Online Access:https://ieeexplore.ieee.org/document/9770808/

Internet

https://ieeexplore.ieee.org/document/9770808/

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