Prediction of methane emissions in coalmine - Soko

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dc.citation.epage87
dc.citation.rankM33
dc.citation.spage84
dc.contributor.authorIvaz, Jelena
dc.contributor.authorPetrović, Dejan
dc.contributor.authorRadovanović, Mladen
dc.contributor.authorZlatanović, Dragan
dc.contributor.authorStojadinović, Saša
dc.contributor.authorStojković, Pavle
dc.date.accessioned2024-01-09T08:42:46Z
dc.date.available2024-01-09T08:42:46Z
dc.date.issued2023
dc.description.abstractMethane in underground mines represents a high level of risk from the aspect of safety and health at work, namely the explosion of this gas is one of the most common causes of major disasters in coal underground mines. The consequences of these accidents are a large number of injured workers as well as material damage, and very often the shutdown of the mines themselves. Methane also has a negative effect on the atmosphere because it creates a greenhouse effect. However, methane, in addition to its negative effects, is also used in the chemical industry as an energy source for mass consumption. The paper presents a method for predicting methane emissions based on an artificial neural network (ANN). The model was created for ten years of data on the amount of methane in the exhaust air for ventilation in the underground coal mine - Soko. This method can very accurately predict methane emissions in coal mines. Data on methane missions have multiple benefits for mines because they enable the prevention of major disasters in mines, as well as the potential exploitation of methane, which would reduce the negative impact on the environment.
dc.identifier.isbn978-86-6305-140-9
dc.identifier.urihttps://ioc.tfbor.bg.ac.rs/public/2023/Proceedings_IOC_2023.pdf
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/5793
dc.language.isoen
dc.publisherUniversity of Belgrade, Technical Faculty in Bor
dc.rights.licenseCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceProceedings - 54th International October Conference on Mining and Metallurgy - IOC 2023, 18-21 October 2023, Bor Lake, Serbia
dc.subjectneural network
dc.subjectmethane
dc.subjectcoal mine
dc.subjectprediction
dc.titlePrediction of methane emissions in coalmine - Soko
dc.typeconferenceObject
dc.type.versionpublishedVersion

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