Özet:

Abstract Context. Quite often, experts are involved in the process of diagnosis and monitoring the technical condition of buildings and structures, and in this case, situations might arise when expert data is generated under some specific types of uncertainty, and their possible combinations. This, in turn, necessitates the development of new approaches aimed at solving the problems of structuring and analytical processing of inaccurate, uncertain, fuzzy expert knowledge. Objective. The methodology for choosing the category of technical condition of construction objects, including buildings and structures, and ranking the corresponding construction objects within the given category of the technical condition according to their degree of danger (expected damage in the event of an emergency) has been proposed in this paper. The proposed approach is based on the expert assessment methods and the mathematical apparatus of the evidence theory, which allows operating correctly with data generated under uncertainty, incompleteness, and inaccuracy. In order to improve the quality of combination results, it is proposed to use one of the proportional conflict redistribution rules and determine the optimal evidence combination order based on metrics in evidence theory. Results. The paper proposes a methodology for the synthesis of group solutions for assessing the technical condition of civil, industrial and military-technical construction objects, and determining objects that primarily need maintenance or overhaul under complex forms of uncertainty and multi-alternatives. Application of the proposed methodology will allow rational distribution of available resources when planning preventive measures and carrying out repair work (overhaul, reconstruction, etc.) to increase the efficiency of their trouble-free operation. Conclusions. The methodology proposed in this study constitutes the theoretical basis for the design of decision support systems for monitoring the technical condition of residential and/or non-residential real estate (buildings, structures) for various purposes. Author Biography A. V. Shved, Petro Mohyla Black Sea National University, Mykolayiv PhD, Associate Professor of the Department of Software Engineering References Kwan A., Ng P. L. Building diagnostic techniques and building diagnosis: the way forward, Engineering Asset

Anahtar Kelimeler: