Artificial neural networks in diagnostic system for purifying fumes installation
Keywords:
artificial intelligence, neural networks, advisory systems, diagnosticsAbstract
The purpose of the paper is to present solution to design additional diagnostic system for, based on cutting-edge technology, purifying fumes installation. Neural networks, which determine the core of the system, were used as predictive models. Designed very efficient neural structures have served to build simulative diagnostic advisory system.
References
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[2] A.G. Chmielewski, E. Iller, Demonstracyjna przemysłowa instalacja usuwania S02 i NOx z gazów odlotowych przy użyciu wiązki elektronów w Elektrowni ,”Pomorzany”. PT J, 41b.3/1998, 37-41, 1998.
[3] A. Cichocki, R. Unbehauen, Neural Networks for Optimization and Signal Processing. Wiley, New York, 1993.
[4] I. Dalmi, L. Kovacs, I. Lorant, G. Terstyanszky, Application of supervised and unsupervised learning methods to fault diagnosis. 14th World Congress of IFAC, 91-96, Beijing, P.R. China, 1999.
[5] S. Haykin, Neural Networks, a Comprehensive Foundation. Macmillan College Publishing Company, New York, 1994.
[2] A.G. Chmielewski, E. Iller, Demonstracyjna przemysłowa instalacja usuwania S02 i NOx z gazów odlotowych przy użyciu wiązki elektronów w Elektrowni ,”Pomorzany”. PT J, 41b.3/1998, 37-41, 1998.
[3] A. Cichocki, R. Unbehauen, Neural Networks for Optimization and Signal Processing. Wiley, New York, 1993.
[4] I. Dalmi, L. Kovacs, I. Lorant, G. Terstyanszky, Application of supervised and unsupervised learning methods to fault diagnosis. 14th World Congress of IFAC, 91-96, Beijing, P.R. China, 1999.
[5] S. Haykin, Neural Networks, a Comprehensive Foundation. Macmillan College Publishing Company, New York, 1994.
Published
2022-08-11
Issue
pp. 531-541
Section
Articles
License
Copyright © The Author(s).
This work is licensed under the Creative Commons Attribution 4.0 International CC BY 4.0.
How to Cite
Bańka, S., & Jaroszewski, K. (2022). Artificial neural networks in diagnostic system for purifying fumes installation. Computer Assisted Methods in Engineering and Science, 14(4), 531-541. https://cames3.ippt.pan.pl/index.php/cames/article/view/782
