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Intelligent Technologies in the Examination of Construction Structures
Author(s) -
Galina G. Kashevarova,
Yury L. Tonkov
Publication year - 2018
Publication title -
academia. arhitektura i stroitelʹstvo
Language(s) - English
Resource type - Journals
ISSN - 2077-9038
DOI - 10.22337/2077-9038-2018-1-92-99
Subject(s) - computer science , identification (biology) , fuzzy logic , objectivity (philosophy) , normative , fuzzy set , basis (linear algebra) , artificial intelligence , risk analysis (engineering) , data mining , mathematics , medicine , philosophy , botany , geometry , epistemology , biology
Categoiy of technical condition (normative, workable imited operational or emergency), which is determined by engineering inspection of buildings and structures, is the main criterion in making decisions about the degree of accident or the need to take measures to bring it to further use. The decisions taken depend on the objectivity and reliability of the information provided ty expertswhich sometimes cannot be interpreted as completely true or complete^ false. It seems advisable to strengthen and expand the professional capabilities of specialists who are engaged in the survey of construction sites through the use of expert systems on the basis of the mathematical apparatus of the theoiy of fuzzy sets and fuzzylogic. This makes it possible to take into account the scatter of individual opinions. Information from the subject area of technical diagnostics of buildings is formalized in terms of fuzzy sets with the use of membership functions created for both input and output control parameters. To implement the fuzzy logical inference, Mamdani's algorithm, modified and adapted to the given problem, was proposed. This technology allows to give a strict mathematical description of vague statements realizing an attempt to overcome alinguistic barrier between a person whose judgments and assessments are approximate and indistinct and a computer that can on^ perform clear instructions. A computer program has been developed that implements the method of identification of the category of technical condition of building structures on the basis of fuzzy knowledge bases.

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