Prototypical investigation of the use of fuzzy measurement data in a case study in water analysis

• Autorzy: Penzel Stefanie , Rudolph Mathias , Borsdorf Helko , Kanoun Olfa

Identyfikatory

DOI

10.15439/2022F125

• Konferencja: 17th Conference on Computer Science and Intelligence Systems
• Języki publikacji: EN

Abstrakty

EN

A common problem when using real data is the fact that the values usually exhibit some degree of uncertainty. Measurement uncertainties therefore represent a major challenge when trying to interpret and draw conclusions from real data. This is especially true in on-site analysis in the environmental sector where the uncertainty in sample plays such a large role. An approach for the modelling and analysis of data for polluted water and the inclusion of measurement uncertainties is presented. This approach is based on fuzzy modelling, in which the uncertainty of the parameters is represented by so-called fuzzy numbers and thus reflect a possible blurred range of these parameter values. The result is a fuzzy pattern classifier, which allows a fuzzy and thus realistic characterization of unknown water samples. The procedure is exemplified using the extinction spectra taken using a UV/Vis spectrometer.

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 31
• Strony: 27--33
• Opis fizyczny: Bibliogr. 16 poz., tab., wykr.

Twórcy

autor

Penzel Stefanie

• Leipzig University of Applied Science Karl-Liebknecht-Str. 132 04277 Leipzig, Germany

autor

Rudolph Mathias

• Leipzig University of Applied Science Karl-Liebknecht-Str. 132 04277 Leipzig, Germany

autor

Borsdorf Helko

• Helmholtz Centre for Environmental Research - UFZ, Department of Monitoring and Exploration Technologies, Permoserstr. 15 Leipzig, Germany

autor

Kanoun Olfa

• University of Technology Chemnitz, Professorship Measurement and Sensor Technology, Reichenhainer Str. 9 Chemnitz, Germany

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).