Pendekatan Baharu untuk Mengelompok Stesen Pengawasan Kualiti Udara menggunakan Homologi Gigih

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dc.contributor.authorNur Fariha Syaqina Zulkepli
dc.contributor.authorMohd Salmi Md Noorani
dc.contributor.authorFatimah Abdul Razak
dc.contributor.authorMunira Ismail
dc.contributor.authorMohd Almie Alias
dc.coverage.publicationMalaysia
dc.date.accessioned2024-05-10T03:25:29Z
dc.date.available2024-05-10T03:25:29Z
dc.date.issued2020
dc.description.abstractThe issue of air pollution is a global problem that continues to be discussed today. Often, the use of quantitative approaches such as cluster analysis, correlation analysis and principal component analysis is used to analyze the similarity of air pollution between stations. However, studies related to qualitative approaches, especially topological approaches to analyzing the similarity of air pollution, have not been widely popularized in Malaysia. Therefore, this study is a pilot study conducted to investigate the similarity of air pollution between several stations in Malaysia using a technique in the topological data analysis known as persistent homology. The topological properties of air pollution are described by topological features such as connected components, holes, and void. The particulate matter (PM10) known as the main pollutant is used to describe the air pollution behavior at Klang, Petaling Jaya and Shah Alam air quality monitoring stations.
dc.identifier.citationZulkepli, N. F. S., Noorani, M. S. M., Razak, F. A., Ismail, M., & Alias, M. A. (2020). A New Approach to Cluster Air Quality Monitoring Stations using Persistent Homology. Sains Malaysiana, 49(4), 963-970.
dc.identifier.urihttps://repoemc.ukm.my/handle/123456789/569
dc.language.isoen
dc.publisherPenerbit UKM
dc.publisher.alternativeSains Malaysiana
dc.subjectPersistent homology
dc.subjectPM10
dc.subjecttopological data analysis
dc.subjecttopological similarity
dc.subjectWasserstein distance
dc.titlePendekatan Baharu untuk Mengelompok Stesen Pengawasan Kualiti Udara menggunakan Homologi Gigih
dc.typeJournal

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