John Sarun VARGHESE

Master's thesis

Binary Classifier to Detect Anomalies in Process Values to Increase Robustness of a PEMS

Abstract:
This thesis aims to increase the resilience of existing Predicive Emission Monitoring Systems (PEMS) by introducing an anomaly detection model which is capable of detecting anomalies based off process values from sensors in power plants.
Abstract:
This thesis aims to increase the resilience of existing Predicive Emission Monitoring Systems (PEMS) by introducing an anomaly detection model which is capable of detecting anomalies based off process values from sensors in power plants.
 
 
Language used: English
Date on which the thesis was submitted / produced: 9. 2. 2024

Thesis defence

  • Supervisor: prof. Dr. Michael Heigl

Citation record

The right form of listing the thesis as a source quoted

VARGHESE, John Sarun. Binary Classifier to Detect Anomalies in Process Values to Increase Robustness of a PEMS. České Budějovice, 2024. diplomová práce (Mgr.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta

Full text of thesis

Contents of on-line thesis archive
Published in Theses:
  • Soubory jsou nedostupné do 9. 2. 2027
  • Po tomto datu bude práce dostupná: světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakulta

UNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE

Faculty of Science

Master programme / field:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science

Theses on a related topic

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