Page 113 - DP-2-2
P. 113

Design+                                                                 Modern interpretations of probability



            allows for obtaining adequate results based on which   as well as the safety and survivability of structurally
            effective decisions can be made, which provided that there   complex objects of long-term use.
            is a sufficient amount of these data. It should be recognized   At the same time, it should be noted that the methods
            that the degree of confidence in the results obtained can be   of fuzzy set theory are not able to fully replace the methods
            assessed by calculating the appropriate confidence intervals.
                                                               and  algorithms  associated  with  specific  calculations,
              However, the application of probability theory is often   which are based on sufficient volume and carefully verified
            associated with the need to make poorly justified (or   statistical material, and are successfully implemented
            not justified at all) simplifications of the analyzed object   in the framework of probability theory and its logical
            (process) model, which significantly reduces the value of   interpretation.
            the obtained results and casts doubt on their adequacy. In
            addition, applying probability theory becomes practically   Acknowledgments
            impossible when the primary data volume is insufficient.   None.
            It should be noted that in many cases (for example, in the
            process of calculating the failure rates of an object), the   Funding
            direct application of probability theory algorithms does   None.
            not take into account the structure of the object under
            study, and is also burdened by the condition of conformity   Conflict of interest
            of the mode of functioning of the components to the
            modes of establishing the corresponding basic indicators   The authors declare that they have no competing interests.
            (e.g.,  failure rates of components). Fundamentally,
            differences in the structure of objects operating under the   Author contributions
            influence of various sets of factors with differing intensities   Conceptualization: Yuri F. Zinkovsky
            should be represented by the same models for applying   Formal analysis: Leonid O. Uryvsky
            probability theory algorithms. This approach can result in   Investigation: All authors
            significant methodological errors in the obtained results.  Methodology: Yuri F. Zinkovsky
              Logical interpretation of probability (in particular,   Writing – original draft: All authors
            probability logic) overcomes some of the methodological   Writing – review & editing: Leonid O. Uryvsky
            difficulties of probability theory. Logical probability allows   Ethics approval and consent to participate
            us to consider the structure of the analyzed object, identify
            potentially dangerous places in such a structure, and   Not applicable.
            consider the possibility of the occurrence and spreading of
            an emergency. It also provides additional opportunities to   Consent for publication
            improve the efficiency of diagnostic algorithms. However,   Not applicable.
            relying on statistical material in calculating the final results
            of the study of probability logic is tightly bound to the   Availability of data
            availability of appropriate statistical data. Obtaining such   Data used in this work are available from the corresponding
            data is often realized in conditions that do not correspond   author on reasonable request.
            to the real conditions of the object’s operation. This can
            significantly distort the obtained conclusions, reducing the   References
            effectiveness of appropriate solutions.
                                                               1.   Rice  John A.  Mathematical Statistics and Data Analysis.
              Fuzzy set theory is adapted for processing small    2   ed. Belmont, California: Wadsworth Publishing
                                                                   nd
            amounts of incomplete and inaccurate information, which   Company; 1995. p. 672. Available from: https://www.scribd.
            can be represented in numerical and non-numerical     com/document/402243105/John-A-Rice-Mathematical-
            forms.  The  corresponding  methods  and  algorithms are   statistics-and-data-an-BookFi-2-pdf
            usually suitable for processing expert opinions, as well as   2.   Bronshtein Ilja N, Semendyayev KA, Musiol G, Heiner M.
            recommendations and suggestions based on the experience   Probability Theory and Mathematical Statistics. Handbook
            and intuition of specialists. At the same time, these experts   of Mathematics. Berlin, Heidelberg: Springer; 2013.
            and specialists can freely and comfortably formulate their   p.  743-794.  Available  from: https://link.springer.com/
            assessments numerically and linguistically. The theory   chapter/10.1007/978-3-662-05382-9_16
            of fuzzy sets is most suitable for establishing “current”   3.   Bernoulli J. The Art of Conjecturing, Together with Letter to
            indicators of operational reliability and residual resource,   a Friend on Sets in Court Tennis. Baltimore, Maryland: The


            Volume 2 Issue 2 (2025)                         18                               doi: 10.36922/dp.6387
   108   109   110   111   112   113   114   115   116   117   118