Fuzzy Probability for System Reliability
Fuzzy fault trees provide a powerful and computationally efficient technique for developing fuzzy probabilities based on independent inputs. The probability of any event that can be described in terms of a sequence of independent unions, intersections, and complements may be calculated by a fuzzy fault tree. Unfortunately, fuzzy fault trees do not provide a complete theory: many events of substantial practical interest cannot be described only by independent operations. In this paper, we introduce a new extension of crisp probability theory. Our model is based on n independent inputs, each with a fuzzy probability. The elements of our sample space describe exactly which of the n input events did and did not occur. Our extension is complete, since a fuzzy probability is assigned to every subset of the sample space. Our extension is also consistent with all calculations that can be arranged as a fault tree.
J. P. Dunyak and D. C. Wunsch, "Fuzzy Probability for System Reliability," Proceedings of the IEEE Conference on Decision and Control, vol. 3, pp. 2934 - 2935, Institute of Electrical and Electronics Engineers (IEEE), Jan 1998.
The definitive version is available at https://doi.org/10.1109/CDC.1998.757925
1998 37th IEEE Conference on Decision and Control (CDC) (1998: Dec. 16-18, Tampa, FL)
Electrical and Computer Engineering
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 1998 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jan 1998