An Input-weighted, Multi-Objective Evolutionary Fuzzy Classifier, for Alcohol Classification

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dc.authoridEKMEKCI, Dursun/0000-0002-9830-7793
dc.contributor.authorShahbazova, Shahnaz N.
dc.contributor.authorEkmekci, Dursun
dc.date.accessioned2024-09-29T16:12:25Z
dc.date.available2024-09-29T16:12:25Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThe success of the evolutionary computational methods in scanning at problem's solution space and the ability to produce robust solutions, are important advantages for fuzzy systems, especially in terms of interpretability and accuracy . Many techniques have been introduced for multi-objective evolutionary fuzzy classifiers by considering this advantage. However, these techniques are mostly fuzzy rule-based methods. In this study, instead of designing an optimal rule table or determining optimal rule weights, the inputs are weighted, and no rules are used. The average of the degrees of membership obtained with their Membership Function (MF) is calculated as the input membership degree (mu Inp) for each input. The mu Inps are then weighted, and a single coefficient is generated to be used for the output. With the output, results are obtained for different objective functions. The weights of the inputs and the MFs parameters of all variables (inputs and outputs) are optimized with NSGA-II. The performance of the method has been tested for alcohol classification. As a result, it has been proven that the method can generate designs that can classify at shallow error levels with different sensors at different gas concentrations. In addition, it has been observed that the proposed method produces more successful solutions for alcohol classification problems when compared to other MOEFC techniques.en_US
dc.identifier.endpage81en_US
dc.identifier.issn1785-8860
dc.identifier.issue10en_US
dc.identifier.startpage61en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/8733
dc.identifier.volume19en_US
dc.identifier.wosWOS:000933574100002en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherBudapest Techen_US
dc.relation.ispartofActa Polytechnica Hungaricaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulti-Objective Fuzzy Classifieren_US
dc.subjectMulti-Objective Optimizationen_US
dc.subjectInput-Weighted Multi-Objective Fuzzy Classifieren_US
dc.titleAn Input-weighted, Multi-Objective Evolutionary Fuzzy Classifier, for Alcohol Classificationen_US
dc.typeArticleen_US

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