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Prediction of Ultraviolet Corrosion Levels of High Density Polyethylene Using Artificial Intelligence

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dc.contributor.authorSeo, J.-
dc.contributor.authorPark, G.-
dc.contributor.authorKim, M.-
dc.contributor.authorJoo, J.-
dc.contributor.authorKoh, J.-
dc.date.accessioned2023-05-15T09:40:09Z-
dc.date.available2023-05-15T09:40:09Z-
dc.date.issued2023-03-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/59427-
dc.description.abstractCurrently, as the intensity of ultraviolet rays increases due to the severe global warming problem, it is difficult to make materials that exclude ultraviolet rays. As a result, high-density polyethylene (HDPE) is a non-toxic ecofriendly plastic with no environmental hormones detected and has been found to have excellent strength and less damage to ultraviolet rays, and interest in eco-friendly ship technology is increasing. This research predicted damage to high-density polyethylene by adding a carbon black sample, which is a UV stabilizer, to HDPE using a long-lasting UV-A lamp because it requires a lot of time due to the presence or absence of ultraviolet limitation. Since it takes a lot of time and money to check the corrosion of the material using ultraviolet rays, research was conducted using artificial intelligence to solve this problem, and as a result, it was confirmed that the degree of corrosion of HDPE according to the irradiation time can be predicted with 90% accuracy. © 2023 IEEE.-
dc.format.extent5-
dc.language영어-
dc.language.isoENG-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titlePrediction of Ultraviolet Corrosion Levels of High Density Polyethylene Using Artificial Intelligence-
dc.typeArticle-
dc.identifier.doi10.1109/CSPA57446.2023.10087881-
dc.identifier.scopusid2-s2.0-85153729074-
dc.identifier.bibliographicCitation2023 19th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2023 - Conference Proceedings, pp 278 - 282-
dc.citation.title2023 19th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2023 - Conference Proceedings-
dc.citation.startPage278-
dc.citation.endPage282-
dc.type.docTypeConference Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorartificial intelligence-
dc.subject.keywordAuthorcarbon black-
dc.subject.keywordAuthorhigh-density polyethylene-
dc.subject.keywordAuthorultra violet Absorber-
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