Bayesian Belief Network in the Analysis of Damage to Prefabricated Large-panel Building Structures in Mining Areas

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dc.contributor.authorRusek, Janusz
dc.contributor.authorFirek, Karol
dc.contributor.organizationAkademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowieen
dc.date.accessioned2017-06-14T10:02:23Z
dc.date.available2017-06-14T10:02:23Z
dc.date.issued2016
dc.description.abstractThe paper presents a methodology for assessing the intensity of damage to the elements of building structures constructed in the large-panel technology, located in mining areas. Bayesian Belief Network was used, which allows to predict the intensity of damage to a building structure, and the probability of its occurrence was predicted. The article also presents the possibility of using the created model for the assessment of damage in the case of incomplete or uncertain decision data. The structure of the Bayesian Belief Network was built on the database regarding the construction, maintenance quality, and intensity of damage to 129 buildings, taking into account environmental effects in the form of mining impacts. The study demonstrates applications of the network for the diagnosis of the causes of damage and for predicting the impacts of mining activities on building structures.en
dc.description.sponsorshipAGH w Krakowie
dc.identifier.citationRusek, Janusz & Firek, Karol. (2016). BAYESIAN BELIEF NETWORK IN THE ANALYSIS OF DAMAGE TO PREFABRICATED LARGE-PANEL BUILDING STRUCTURES IN MINING AREAS. Polish Journal of Environmental Studies. 25. 77-82.
dc.identifier.issn1230-1485
dc.identifier.urihttps://open.icm.edu.pl/handle/123456789/12468
dc.language.isoen
dc.publisherFirma Wydawnicza HARD s.c. Jerzy Radecki Hanna Radeckaen
dc.rightsDozwolony użytek*
dc.subjectdamage to large-panel building structuresen
dc.subjectmining impactsen
dc.subjectBayesian Belief Networken
dc.titleBayesian Belief Network in the Analysis of Damage to Prefabricated Large-panel Building Structures in Mining Areasen
dc.title.alternativeSieć przekonań Bayesa w analizie stanu uszkodzeń budynków wielkoblokowych na terenach górniczychpl
dc.typearticleen
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