Bayes Conditional Probability of Fuzzy Damage and Technical Wear of Residential Buildings

Autor: Jarosław Konior, Tomasz Stachoń
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Applied Sciences, Vol 11, Iss 6, p 2518 (2021)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app11062518
Popis: The purpose of the research presented in the article is to identify the impact of the processes associated with the broadly understood maintenance of old residential buildings with a traditional construction on the size and intensity of the wear of their elements. The goal was achieved by analyzing the symptoms of the technical wear process, which involved the understanding of the mechanism of the occurrence of the phenomenon of damage, and the identification of the size and intensity of the damage to the elements of the evaluated buildings. The consequence of systematizing the most important processes that influence the loss of functional properties of residential buildings was the creation of the authors’ own qualitative model and its transformation into a quantitative model. This, in turn, enabled a multi-criteria quantitative analysis of the cause and effect phenomena—“damage-technical wear”—of the most important elements of downtown tenement buildings to be carried out in fuzzy conditions, i.e., uncertainty concerning the occurrence of damage and the wear process. The following key question was answered in the subjective expert assessment of the technical condition of an evaluated residential building: what is the probability of the wear of an element, which may be more or less correlated with its average maintenance conditions, or more simply, what is the probability that the element is more or less (approximately) worn? It has been proven that the conditional probability of the technical wear of an element in relation to its damage increases with the deterioration of the maintenance conditions of the building, and this increase is very regular, even in the case of different building elements. This probability is characterized by a low standard deviation and a narrow range of the dispersion of results in the case of various elements with regards to each of the considered building maintenance conditions.
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