Evaluation of waste management using clustering algorithm in megacity Istanbul

MakaleAçık Erişim
  • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
  • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
  • SDG 12 · Sorumlu Üretim ve Tüketim

Özet

Industrialization and urbanization are increasing with the effect of globalization worldwide. The waste management problems are rising with the rising population rate, industrialization, and economic developments in the cities, which turned into environmental problems that directly affect human health. This study aims to examine waste management performance in the districts located in the city of Istanbul. To ensure that the districts are clustered in terms of the similarities and differences base on waste management. On this occasion, the authorized unit managers of the districts in the same cluster will be able to establish similar management policies and make joint decisions regarding waste management. In addition, the division of districts into clusters according to the determining indicators can provide information about the locations of waste storage centers. Also, these clusters will form the basis for the optimization constraints required to design appropriate logistics networks. Waste management performance of 39 districts in Istanbul in 2019 was compared by taking into consideration domestic waste, medical waste, population, municipal budget, and mechanical sweeping area. The data were obtained from The Istanbul Metropolitan Municipality (IMM) and Turkey Statistical Institute (TURKSTAT). One of the non-hierarchical clustering methods, the K-means clustering method, was applied using IBM SPSS Modeler data mining software to determine the relations between 39 districts. As a result, the waste management performance of the districts was evaluated according to the statistical data, similarities and differences were revealed by using the determined indicators.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/bayburt/12195Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.35208/ert.764363Yayıncı resmi DOI adresi
İndeks kayıtları
Kaydın indeks veri tabanlarındaki sayfası (aktarımda alınan kayıt numarasıyla). Erişim, indeksin kendi koşullarına bağlıdır.
Atıflar
Scopus
12
OpenAlex
11
TR Dizin
1
Her kaynağın kendi saydığı toplam atıf; aktarım ve zenginleştirme sırasında alındı.
Tam Kayıt
AlanDeğerDil
dc.contributor.authorGuleryuz, Didem
dc.date.accessioned2026-10-29T19:09:18.395300857Z
dc.date.available2026-10-29T19:09:18.395300857Z
dc.date.issued2020
dc.description.abstractIndustrialization and urbanization are increasing with the effect of globalization worldwide. The waste management problems are rising with the rising population rate, industrialization, and economic developments in the cities, which turned into environmental problems that directly affect human health. This study aims to examine waste management performance in the districts located in the city of Istanbul. To ensure that the districts are clustered in terms of the similarities and differences base on waste management. On this occasion, the authorized unit managers of the districts in the same cluster will be able to establish similar management policies and make joint decisions regarding waste management. In addition, the division of districts into clusters according to the determining indicators can provide information about the locations of waste storage centers. Also, these clusters will form the basis for the optimization constraints required to design appropriate logistics networks. Waste management performance of 39 districts in Istanbul in 2019 was compared by taking into consideration domestic waste, medical waste, population, municipal budget, and mechanical sweeping area. The data were obtained from The Istanbul Metropolitan Municipality (IMM) and Turkey Statistical Institute (TURKSTAT). One of the non-hierarchical clustering methods, the K-means clustering method, was applied using IBM SPSS Modeler data mining software to determine the relations between 39 districts. As a result, the waste management performance of the districts was evaluated according to the statistical data, similarities and differences were revealed by using the determined indicators.
dc.identifier.doi10.35208/ert.764363
dc.identifier.eissn2636-8498
dc.identifier.endpage112
dc.identifier.issn2636-8498
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85126420887
dc.identifier.startpage102
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/12195
dc.identifier.volume3
dc.language.isoen
dc.publisherYildiz Technical University
dc.relation.ispartofEnvironmental Research and Technology
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectclustering
dc.subjectdata mining
dc.subjectK-means
dc.subjectWaste management
dc.titleEvaluation of waste management using clustering algorithm in megacity Istanbul
dc.typeArticle
rdl.citation.openalex11
rdl.citation.scopus12
rdl.citation.trdizin1
rdl.oa.statusgold
rdl.oa.urlhttps://dergipark.org.tr/en/download/article-file/1244065
rdl.sdgSDG11
rdl.sdgSDG12
rdl.sdgSDG09
rdl.source.indexSCOPUS
rdl.source.indexTRDIZIN