NDLI: A Summary on Fuzzy Probability Theory

Content Provider	IEEE Xplore Digital Library
Author	Beer, M.
Copyright Year	2010
Abstract	Fuzzy probability theory is an extension of probability theory to dealing with mixed probabilistic/non-probabilistic uncertainty. It provides a theoretical basis to model uncertainty which is only partly characterized by randomness and defies a pure probabilistic modeling with certainty due to a lack of trustworthiness or precision of the data or a lack of pertinent information. The fuzzy probabilistic model is settled between the probabilistic model and non-probabilistic uncertainty models. The significance of fuzzy probability theory lies in the treatment of the elements of a population not as crisp quantities but as set-valued quantities or granules in an imprecise manner, which largely complies with reality in most everyday situations. Probabilistic and non-probabilistic uncertainty and imprecision can so be transferred adequately and separately to the results of a subsequent analysis. This enables best case and worst case estimates in terms of probability taking account of variations within the inherent non-probabilistic uncertainty. The development of fuzzy probability theory was initiated by H. Kwakernaak with the introduction of fuzzy random variables in [15] in 1978. The usefulness of the theory has been underlined with various applications beyond mathematics and computer science. An increasing interest in fuzzy probabilities and related concepts has been developed, in particular, in engineering. In this summary, a general introduction to fuzzy probability theory is given. Detailed mathematical descriptions and discussions in an engineering context are provided in [1].
Starting Page	5
Ending Page	6
File Size	120332
Page Count	2
File Format	PDF
ISBN	9781424479641
DOI	10.1109/GrC.2010.78
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	fuzzy random variables Fuzzy sets Uncertainty imprecise data Probabilistic logic Reliability engineering imprecise probabilities Random variables Safety fuzzy probabilities
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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