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Ranking of elements in system reliability modeling: The least influence method
Author(s) -
Rothstein Alexander,
Dreyfuss Michael
Publication year - 2018
Publication title -
systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 50
eISSN - 1520-6858
pISSN - 1098-1241
DOI - 10.1002/sys.21450
Subject(s) - ranking (information retrieval) , disjoint sets , similarity (geometry) , data mining , mathematics , fuzzy set , reliability (semiconductor) , independence (probability theory) , element (criminal law) , transitive closure , fuzzy logic , computer science , artificial intelligence , theoretical computer science , algorithm , discrete mathematics , statistics , power (physics) , physics , quantum mechanics , political science , law , image (mathematics)
In this paper, we propose a new method of elements ranking in system reliability design using the theory of fuzzy relations. The problem is formulated as an automatic classification based on the transitive closure of the fuzzy similarity relations. This allows splitting the set of system elements into disjoint classes, which are similar in importance. To define the fuzzy relations of similarity we present the parameters of each element as a vector of influences. To measure the similarity of elements, we use the distance between the two vectors and for the degree of influence evaluation, we present a special algorithm using the expert knowledge about the least impact of an element and about the comparisons to the other influences using the 9‐point Saaty scale. The proposed method relaxes the assumption about the independence and the binary state (up/down) of elements. The possible fields of application are systems with ill‐defined structures and multifunctional elements such as organizational, ergatic, military, political, and other complex systems.