Publication Details

Category Text Publication
Reference Category Book chapters
DOI 10.1007/978-3-031-39777-6_22
Title (Primary) Application of a fuzzy based machine learning aApproach to the detection of harmful algae in water monitoring
Title (Secondary) Intelligent and Fuzzy Systems. Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, Volume 2
Author Penzel, S.; Rudolph, M.; Borsdorf, H. ORCID logo ; Kanoun, O.
Publisher Kahraman, C.; Sari, I.C.; Oztaysi, B.; Cebi, S.; Onar, S.C.; Tolga, A.Ç.
Source Titel Lecture Notes in Networks and Systems
Year 2023
Department MET
Volume 759
Page From 181
Page To 188
Language englisch
Topic T5 Future Landscapes
Abstract This paper introduces a new approach for the detection of harmful algae in water monitoring with the application of a fuzzy based machine learning methodic by fuzzily describing the data after feature extraction from the water spectra. The main challenge of this task was to describe the whole transmission and fluorescence spectra to extract the features and build a multidimensional fuzzy pattern classifier that integrates the measurement uncertainties associated with the measurement. The utility and application of such a methodic is to detect with light sensors harmful algae in water monitoring before, for example, algae can pollute the water or toxic algal blooms can cause harm. Using different solutions of a reference substance for alga within chlorophyll a data basis for the learning phase of a classification was generated with the feature extraction. The result is a highly flexible classifier which provides information about unknown spectral data and indicates a possible need for action.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29526
Penzel, S., Rudolph, M., Borsdorf, H., Kanoun, O. (2023):
Application of a fuzzy based machine learning aApproach to the detection of harmful algae in water monitoring
In: Kahraman, C., Sari, I.C., Oztaysi, B., Cebi, S., Onar, S.C., Tolga, A.Ç. (eds.)
Intelligent and Fuzzy Systems. Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, Volume 2
Lecture Notes in Networks and Systems 759
Springer, Cham, p. 181 - 188 10.1007/978-3-031-39777-6_22