Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/52315
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dc.contributor.authorNamazi, Samiraen
dc.contributor.authorBrankovic, Ljiljanaen
dc.contributor.authorMoghtaderi, Behdaden
dc.contributor.authorZanganeh, Jafaren
dc.date.accessioned2022-05-25T02:55:36Z-
dc.date.available2022-05-25T02:55:36Z-
dc.date.issued2020-
dc.identifier.citationProceedings of the Confluence 2020: 10th International Conference on Cloud Computing, Data Science & Engineering:en
dc.identifier.isbn9781728127910en
dc.identifier.isbn9781728127927en
dc.identifier.urihttps://hdl.handle.net/1959.11/52315-
dc.description.abstract<p>Global warming is a long-term environmental hazard demonstrated by a gradual increase in the temperature of the Earth. It is caused by the accumulation of greenhouse gases in the atmosphere, including carbon dioxide and methane. Although, in terms of the volume, methane is considered secondary to carbon dioxide, it is about 21 times more damaging when compared over a 100-year period. Fugitive methane emissions from underground coal mines significantly contribute to global warming. Amongst all the known methods to reduce the fugitive methane, application of thermal oxidation (or, simply, burning) is deemed the most effective and practical. This process produces water vapour and carbon dioxide, which has significantly lower adverse impact on the atmosphere than methane. The thermal oxidisers operate at high temperatures, which may introduce a risk of fire and explosion to the mine. In order to mitigate such risk, a thorough understanding of the methane explosion characteristics is essential. Methane fire and explosion experiments under conditions pertinent to underground coal mines are expensive, risky and necessitate significant effort, and thus require enormous preparation and safety procedures. It is cheaper and safer to analyse existing data to discover patterns and predict explosions than to conduct new extensive experiments. In this paper, we present a comparative study of data mining and machine learning techniques used for these purposes.</p>en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartofProceedings of the Confluence 2020: 10th International Conference on Cloud Computing, Data Science & Engineering:en
dc.titleComparative Study of Data Mining Techniques for Predicting Explosions in Coal Minesen
dc.typeConference Publicationen
dc.relation.conferenceConfluence 2020: 10th International Conference on Cloud Computing, Data Science & Engineeringen
dc.identifier.doi10.1109/Confluence47617.2020.9057921en
local.contributor.firstnameSamiraen
local.contributor.firstnameLjiljanaen
local.contributor.firstnameBehdaden
local.contributor.firstnameJafaren
local.profile.schoolSchool of Science and Technologyen
local.profile.emaillbrankov@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference29th - 31st January, 2020en
local.conference.placeNoida, Indiaen
local.publisher.placeLos Alamitos, United States of Americaen
local.contributor.lastnameNamazien
local.contributor.lastnameBrankovicen
local.contributor.lastnameMoghtaderien
local.contributor.lastnameZanganehen
dc.identifier.staffune-id:lbrankoven
local.profile.orcid0000-0002-5056-4627en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/52315en
local.date.onlineversion2020-04-09-
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleComparative Study of Data Mining Techniques for Predicting Explosions in Coal Minesen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsConfluence 2020: 10th International Conference on Cloud Computing, Data Science & Engineering, Noida, India, 29th - 31st January, 2020en
local.search.authorNamazi, Samiraen
local.search.authorBrankovic, Ljiljanaen
local.search.authorMoghtaderi, Behdaden
local.search.authorZanganeh, Jafaren
local.uneassociationNoen
local.atsiresearchNoen
local.conference.venueAmity Universityen
local.sensitive.culturalNoen
local.identifier.wosid000571173300129en
local.year.available2020en
local.year.published2020en
local.subject.for2020480204 Mining, energy and natural resources lawen
local.subject.seo2020170601 Coal mining and extractionen
local.date.start2020-01-29-
local.date.end2020-01-31-
local.profile.affiliationtypeUnknownen
local.profile.affiliationtypeUnknownen
local.profile.affiliationtypeUnknownen
local.profile.affiliationtypeUnknownen
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School of Science and Technology
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