Type-2 fuzzy logic systems in applications: managing data in selective catalytic reduction for air pollution prevention

• Autorzy: Niewiadomski Adam , Kacprowicz Marcin

Identyfikatory

DOI

10.2478/jaiscr-2021-0006

• Języki publikacji: EN

Abstrakty

EN

The article presents our research on applications of fuzzy logic to reduce air pollution by DeNOx filters. The research aim is to manage data on Selective Catalytic Reduction (SCR) process responsible for reducing the emission of nitrogen oxide (NO) and nitrogen dioxide (NO2). Dedicated traditional Fuzzy Logic Systems (FLS) and Type-2 Fuzzy Logic Systems (T2FLS) are proposed with the use of new methods for learning fuzzy rules and with new types of fuzzy implications (the so-called ”engineering implications”). The obtained results are consistent with the results provided by experts. The main advantage of this paper is that type-2 fuzzy logic systems with ”engineering implications” and new methods of learning fuzzy rules give results closer to expert expectations than those based on traditional fuzzy logic systems. According to the literature review, no T2FLS were applied to manage DeNOx filter prior to the research presented here.

Słowa kluczowe

EN

Selective Catalytic Reduction; SCR; fuzzy management of DeNOx filter; fuzzy logic systems; fuzzy implication; learning fuzzy rules

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2021
• Tom: Vol. 11, No. 2
• Strony: 85--97
• Opis fizyczny: Bibliogr. 38 poz., rys.

Twórcy

autor

Niewiadomski Adam

• Institute of Information Technology, Lodz University of Technology, Wólcza´nska 215, 90-924 Łódź, Poland

autor

Kacprowicz Marcin

• Institute of Information Technology, Lodz University of Technology, Wólcza´nska 215, 90-924 Łódź, Poland

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).