ARTIFICIAL INTELLIGENCE CAPABILITIES FOR INCREASING ORGANIZATIONAL-TECHNOLOGICAL RELIABILITY OF CONSTRUCTION
Journal: Вестник МГСУ / Vestnik MGSU (Vol.13, No. 1)Publication Date: 2018-01-12
Authors : Ginzburg Alexander Vital evich; Ryzhkova Anastasiya Igorevna;
Page : 7-13
Keywords : construction; potential risks; investment; organizational and technological reliability; artificial intelligence; “pure” risks;
Abstract
The technology of artificial intelligence is actively being mastered in the world but there is not much talk about the capabilities of artificial intelligence in construction industry and this issue requires additional elaboration. As a rule, the decision to invest in a particular construction project is made on the basis of an assessment of the organizational and technological reliability of the construction process. Artificial intelligence can be a convenient quality tool for identifying, analyzing and subsequent control of the “pure” risks of the construction project, which not only will significantly reduce the financial and time expenditures for the investor’s decision-making process but also improve the organizational-technological reliability of the construction process as a whole. Subject: the algorithm of creation of artificial intelligence in the field of identification and analysis of potential risk events is presented, which will facilitate the creation of an independent analytical system for different stages of construction production: from the sketch to the working documentation and conduction of works directly on the construction site. Research objectives: the study of the possibility, methods and planning of the algorithm of works for creation of artificial intelligence technology in order to improve the organizational-technological reliability of the construction process. Materials and methods: the developments in the field of improving the organizational and technological reliability of construction were studied through the analysis and control of potential “pure” risks of the construction project, and the work was also carried out to integrate the technology of artificial intelligence into the area being studied. Results: An algorithm for creating artificial intelligence in the field of identification of potential “pure” risks of construction projects was presented. Conclusions: the obtained results are useful for working out practical steps for mastering the technology of artificial intelligence in order to improve the organizational and technological reliability of the construction process.
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