• A. V. Shved Petro Mohyla Black Sea National University, Mykolayiv



Еvidence theory, technical condition category, ranking, expert judgments, uncertainty.


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


Kwan A., Ng P. L. Building diagnostic techniques and building diagnosis: the way forward, Engineering Asset

Management – Systems, Professional Practices and Certification, 2015, Vol. 19, pp. 849–862.

DOI: 10.1007/978-3-319-09507-3_74

Vilhena A., Pedro J. B., Brito J. Comparison of methods used in European countries to assess buildings’ condition,

Proceedings of the 12th International Conference on Durability of Building Materials and Components, 2011,

Porto, pp. 1–7. DOI: 10.13140/RG.2.1.3460.7124

Mitra G., Jain K. K., Bhattacharjee B. Condition assessment of corrosion distressed reinforced concrete buildings using

fuzzy logic, Journal of Performance of Constructed Facilities, 2010, Vol. 24, No. 6, pp. 652–569.

DOI: 10.1061/(ASCE)CF.1943-5509.0000137

Holicky M., Navarova V., Gottfried R., Kronika M., Markova J., Sykora M., Jung K. Basics for assessment of

existing structures. Prague, Klokner Institute, Czech Technical University, 2013, 109 p.

Wahida R., Milton G., Hamadan N. et al. Building condition assessment imperative and process, Procedia – Social and

Behavioral Sciences, 2012, Vol. 65, pp. 775–780. DOI: 10.1016/j.sbspro.2012.11.198

Hamdia K. M., Arafa M., Alqedra M. Structural damage assessment criteria for reinforced concrete buildings by

using a Fuzzy Analytic Hierarchy Process, Underground Space, 2018, Vol. 3, No. 3, pp. 243–249.

DOI: 10.1016/j.undsp.2018.04.002

Gao Z., Li J. Fuzzy Analytic Hierarchy Process evaluation method in assessing corrosion damage of reinforced

concrete bridges, Civil Engineering Journal, 2018, Vol. 4, No. 4, pp. 843–856. DOI: 10.28991/cej-0309138

Rashidi M., Gibson P. A methodology for bridge condition evaluation, Journal of Civil Engineering and Architecture,

, Vol. 6, No. 9, pp. 1149–1157. DOI: 10.17265/1934-7359/2012.09.007

Ter Berg C. J. A., Leontaris G., Van den Boomen M. et al. Expert judgments based maintenance decision support

method for structures with a long service-life, Structure and Infrastructure Engineering, 2019, Vol. 15, No. 4, pp. 492–

DOI: 10.1080/15732479.2018.1558270

Grigorovskiy P., Terentyev O., Mikautadze R. Development of the technique of expert assessment in the diagnosis of the

technical condition of buildings, Technology Audit and Production Reserves, 2017, No. 2, pp. 10–15.

DOI: 10.15587/2312-8372.2018.128548

Abbott G. R., Mc Duling J. J., Parsons S. at el. Building condition assessment: a performance evaluation tool towards

sustainable asset management, Proceedings of the 2007 CIB World building Congress: Construction for Development,

Cape Town, 2007, pp. 649–662.

Jo H. W., Jung I. S., Lee C. S. Fuzzy based condition assessment model prototype of middle and small-size

buildings, Proceedings of the 28th International Symposium on Automation and Robotics in Construction (ISARC),

Seoul, 2011, pp. 1330–1331. DOI: 10.22260/ISARC2011/0246

Terentyev O., Malyna B. Expert information system for decision support for the problem of diagnostics of technical

condition of buildings, International Journal of Science and Research, 2015, Vol. 4, No. 10, pp. 652–654.

Chen Z., Clements-Croome D., Bakker H. H. C. at el. A remote expert system for building diagnosis, Proceedings of

the 8th International Conference and Exhibition on Healthy Buildings: Creating a Healthy Indoor Environment for

People, Lisboa, 2006, pp. 99–104.

Dempster A. P. Upper and lower probabilities induced by a multi–valued mapping, Annals of Mathematical Statistics,

, Vol. 38, pp. 325–339.

Shafer G. A mathematical theory of evidence. Princeton, Princeton University Press, 1976, 297 p.

Beynon M. J., Curry B., Morgan P. The Dempster-Shafer theory of evidence: an alternative approach to multicriteria

decision modeling, Omega, 2000, Vol. 28, No. 1, pp. 37–50.

Jousselme A. L., Grenier D., Boss´e E. A new distance between two bodies of evidence, Information Fusion, 2001,

Vol. 2, pp. 91–101.

Smarandache F. Advances and applications of DSmT for information fusion. Vol. 1. Rehoboth, American Research

Press, 2004, 760 p.

Saaty Т. The Analytic Hierarchy Process: panning, priority setting, resource allocation. Front cover. New York,

McGraw Hill, 1980, 287 p.

Velychko O. M., Gordiyenko T. B., Kolomiets L. V. Methodologies of expert’s competence evaluation and group

expert evaluation, Metallurgical and Mining Industry, 2015, Vol. 7, No. 2, pp. 262–271.

Velychko O. M., Gordiyenko T. B., Kolomiets L. V. Comparative analysis of the assessment results of the

competence of technical experts by different methods, Eastern-European Journal of Enterprise Technologies,

, Vol. 4, No. 3 (88), pp. 4–10. DOI: 10.15587/1729-4061.2017.106825

Borissova D. A group decision making model considering experts competency: An application in personnel selection,

Comptes Rendus de l’Academie Bulgare des Sciences:Sciences Mathematiques et Naturelles, 2018, Vol. 71,

No. 11, pp. 1520–1527. DOI: 10.7546/CRABS.2018.11.11

Becker J., Becker A., Salabun W. Construction and use of the ANP decision model taking into account the experts’

competence, Procedia Computer Science, 2017, Vol. 112, pp. 2269–2279. DOI: 10.1016/j.procs.2017.08.145




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Neuroinformatics and intelligent systems