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Alarm Prediction in Industrial Processes by adityasptr.work is a document available to read on EtoBox.

What is Alarm Prediction in Industrial Processes about?

This paper presents a study on alarm prediction and classification in industrial processes using supervised machine learning techniques, specifically focusing on a case study in an Algerian gas plant. The authors developed a Random Forest model that outperformed other classifiers in accuracy (98.32%) and F1-Score (0.988), while addressing the challenges of alarm floods that hinder operator response during critical situations. The findings highlight the potential of machine learning to enhance alarm manageme

Author
adityasptr.work
Language
EN