Neural network-based data-driven modelling of anomaly detection in thermal power plant-Reference-Cited by-同舟云学术

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Neural network-based data-driven modelling of anomaly detection in thermal power plant

Published:2017-01-02 Issue:1 Volume:58 Page:69-79
ISSN:0005-1144
Container-title:Automatika
language:en
Short-container-title:Automatika

Author:

Banjanovic-Mehmedovic Lejla¹^ORCID,Hajdarevic Amel²,Kantardzic Mehmed³,Mehmedovic Fahrudin⁴,Dzananovic Izet⁵

Affiliation:

1. Department of Automation and Robotics, Faculty of Electrical Engineering, University of Tuzla, Tuzla, Bosnia and Herzegovina

2. Ricardo Prague, Prague, Czech Republic.

3. Speed School of Engineering, University of Louisville, Louisville, KY, U.S.A

4. ABB Representation for Bosnia and Herzegovina, Tuzla, Bosnia and Herzegovina

5. JP Elektroprivreda BiH–Power Plant Tuzla, Tuzla, Bosnia and Herzegovina

Publisher

Informa UK Limited

Subject

General Computer Science,Control and Systems Engineering

Link

https://tandfonline.com/doi/pdf/10.1080/00051144.2017.1343328

Reference27 articles.

1. APPLICATION OF MONITORING, DIAGNOSIS, AND PROGNOSIS IN THERMAL PERFORMANCE ANALYSIS FOR NUCLEAR POWER PLANTS

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2. Literature review deep learning anomaly detection method in power plant based on its data characteristic;AIP Conference Proceedings;2024

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4. Detecting anomalies and de-noising monitoring data from sensors: A smart data approach;Advanced Engineering Informatics;2023-01

5. AI-Based Anomaly Detection on IoT Data-Driven Thermal Power Plants for Condition Monitoring and Preventive Maintenance;Artificial Intelligence in Cyber Security: Theories and Applications;2023

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