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Review of XAI methods for application in heavy industry

creativeworkseries.issn2720-4081
dc.contributor.authorJędrysik, Wojciech
dc.contributor.authorHajder, Piotr
dc.contributor.authorRauch, Łukasz
dc.date.available2025-06-18T04:54:15Z
dc.date.issued2025
dc.descriptionBibliogr. s. 42-43.
dc.description.abstractIn recent years, considerable progress has been made in the field of artificial intelligence and machine learning. This progress allows us to solve increasingly complex problems, but it also requires providing appropriate explanations to understand the actions taken by AI. For this purpose, research into the development of Explainable Artificial Intelligence has been initiated and interest in this topic is constantly growing. This review of XAI methods includes a justification for the need to introduce solutions to explain artificial intelligence models, describes the differences between various methods and presents example method/s that work in different cases. The purpose of this paper is to solve a real problem occurring in heavy industry. The third chapter describes the challenges to be faced, the solution developed and the results of the work. The entire study concludes with a summary of the research findings.en
dc.description.placeOfPublicationKraków
dc.description.versionwersja wydawnicza
dc.identifier.doihttps://doi.org/10.7494/cmms.2025.1.1013
dc.identifier.eissn2720-3948
dc.identifier.issn2720-4081
dc.identifier.urihttps://repo.agh.edu.pl/handle/AGH/113253
dc.language.isoeng
dc.publisherWydawnictwa AGH
dc.relation.ispartofComputer Methods in Materials Science
dc.rightsAttribution 4.0 International
dc.rights.accessotwarty dostęp
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcode
dc.subjectexplainable artificial intelligenceen
dc.subjectmachine learningen
dc.subjectheavy industryen
dc.titleReview of XAI methods for application in heavy industryen
dc.title.relatedComputer Methods in Materials Scienceen
dc.typeartykuł
dspace.entity.typePublication
publicationissue.issueNumberNo. 1
publicationissue.paginationpp. 31-43
publicationvolume.volumeNumberVol. 25
relation.isAuthorOfPublication87602c08-d22a-49b6-b084-8e23902c757c
relation.isAuthorOfPublication05a6e16d-f323-4f88-b25d-f0d5e7295869
relation.isAuthorOfPublication.latestForDiscovery87602c08-d22a-49b6-b084-8e23902c757c
relation.isJournalIssueOfPublication99e6b77f-39f0-4c5d-bac4-ef4869462d6c
relation.isJournalIssueOfPublication.latestForDiscovery99e6b77f-39f0-4c5d-bac4-ef4869462d6c
relation.isJournalOfPublication1f717eff-e164-4db5-8437-ca75e714cac5

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