Firefly-Based feature selection algorithm method for air pollution analysis for Zonguldak region in Turkey

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dc.contributor.authorEşsiz, Esra Saraç
dc.contributor.authorKılıç, Vahide Nida
dc.contributor.authorOturakçı, Murat
dc.date.accessioned2025-01-06T17:30:24Z
dc.date.available2025-01-06T17:30:24Z
dc.date.issued2023
dc.description.abstractAir pollution in cities is a serious environmental issue. In Turkey, the air quality index values of the measurement stations are calculated according to European Union standards. There are many kinds of measurement parameters (features) and 6 different kinds of air quality classes according to measurement stations in Turkey. Non-valuable features can be eliminated effectively with feature selection methods without any performance loss in classification. This study aims to investigate, analyze and implement a feature selection method using the FireFly Optimization Algorithm (FOA) approach. In the study, data from measurement stations for the Zonguldak region, which is known as the most polluted region in Turkey, are obtained and analyzed. Along with the acquired data, new features have been added such as day type day slots and the Covid19 feature since it is thought that curfew restrictions have an impact on air quality. The results were compared with a filter-based feature selection algorithm namely ReliefF. Experimental results show that FOA based feature selection method outperforms the ReliefF method at classification using the Random Forest classifier for air pollution even if with a fewer number of features. The Macro averaged F-score of the data set is increased from 0.685 to 0.988 using the FOA-based feature selection method. © Author(s) 2023.
dc.identifier.doi10.31127/tuje.1005514
dc.identifier.endpage24
dc.identifier.issn2587-1366
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85167574188
dc.identifier.scopusqualityQ3
dc.identifier.startpage17
dc.identifier.trdizinid1180988
dc.identifier.urihttps://doi.org/10.31127/tuje.1005514
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1180988
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1578
dc.identifier.volume7
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherMurat Yakar
dc.relation.ispartofTurkish Journal of Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectAir Pollution Analysis
dc.subjectCovid19
dc.subjectFeature Selection
dc.subjectMachine Learning
dc.titleFirefly-Based feature selection algorithm method for air pollution analysis for Zonguldak region in Turkey
dc.typeArticle

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