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dc.contributor.authorDavid, Jiří
dc.contributor.authorŠvec, Pavel
dc.contributor.authorGarzinová, Romana
dc.contributor.authorKluska-Nawarecka, Stanisława
dc.contributor.authorWilk-Kołodziejczyk, Dorota
dc.contributor.authorRegulski, Krzysztof
dc.date.accessioned2016-06-15T12:59:56Z
dc.date.available2016-06-15T12:59:56Z
dc.date.issued2016
dc.identifier.citationArchives of Civil and Mechanical Engineering. 2016, vol. 16, issue 2, p. 179-185.cs
dc.identifier.issn1644-9665
dc.identifier.urihttp://hdl.handle.net/10084/111664
dc.description.abstractIn the first part of this paper will be described an analysis of control problems and technical lifetime modeling of continuous casting device crystallizers. A full exploitation of continuous casting equipment (CCE) advantages can only be achieved through a control system that minimizes all undesirable effects on the technological process. Some of the undesirable effects influencing the CCE process effectiveness are the failures and service interruptions. This problem was solved by connection of dependability theory and artificial neural networks. The second part of the article refers to a model in linguistic form used to identify the type of defects present in the tested casting. This model, having the form of an attribute table, has been based on the concepts taken from the theory of rough sets and fuzzy logic. A methodology for construction of a heuristic model of linguistic knowledge was presented along with an example of its implementation based on the use of distributed sources of knowledge.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesArchives of Civil and Mechanical Engineeringcs
dc.relation.urihttp://dx.doi.org/10.1016/j.acme.2015.10.006cs
dc.rightsCopyright © 2015 Politechnika Wrocławska. Published by Elsevier Sp. z o.o. All rights reserved.cs
dc.subjectmodelingcs
dc.subjectwearcs
dc.subjectartificial neural networkscs
dc.subjectidentification of the defects in castingscs
dc.subjectattribute tablecs
dc.titleHeuristic modeling of casting processes under the conditions uncertaintycs
dc.typearticlecs
dc.identifier.doi10.1016/j.acme.2015.10.006
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume16cs
dc.description.issue2cs
dc.description.lastpage185cs
dc.description.firstpage179cs
dc.identifier.wos000375730900001


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