Details
Original language | English |
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Title of host publication | Vulnerability, Uncertainty, and Risk |
Subtitle of host publication | Analysis, Modeling, and Management - Proceedings of the ICVRAM 2011 and ISUMA 2011 Conferences |
Pages | 53-61 |
Number of pages | 9 |
Publication status | Published - Apr 2011 |
Externally published | Yes |
Event | International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2011 and the International Symposium on Uncertainty Modeling and Analysis, ISUMA 2011 - Hyattsville, MD, United States Duration: 11 Apr 2011 → 13 Apr 2011 |
Publication series
Name | Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management - Proceedings of the ICVRAM 2011 and ISUMA 2011 Conferences |
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Abstract
Predicting the behavior and reliability of engineering structures and systems is often plagued by uncertainty and imprecision caused by sparse data, poor measurements and subjective information. Accounting for such limitations complicates the mathematical modeling required to obtain realistic results in engineering analyses. The framework of imprecise probabilities provides a mathematical basis to deal with these problems which involve both probabilistic and non-probabilistic sources of uncertainty. A common feature of the various concepts of imprecise probabilities is the consideration of an entire set of probabilistic models in one analysis. But there are differences between the concepts in the mathematical description of this set and in the theoretical connection to the probabilistic models involved. This study is focused on fuzzy probabilities, which combine a probabilistic characterization of variability with a fuzzy characterization of imprecision. We discuss how fuzzy modeling can allow a more nuanced approach than interval-based concepts. The application in an engineering analysis is demonstrated by means of an example.
ASJC Scopus subject areas
- Engineering(all)
- Safety, Risk, Reliability and Quality
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Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management - Proceedings of the ICVRAM 2011 and ISUMA 2011 Conferences. 2011. p. 53-61 (Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management - Proceedings of the ICVRAM 2011 and ISUMA 2011 Conferences).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Fuzzy probability in engineering analyses
AU - Beer, M.
AU - Ferson, S.
PY - 2011/4
Y1 - 2011/4
N2 - Predicting the behavior and reliability of engineering structures and systems is often plagued by uncertainty and imprecision caused by sparse data, poor measurements and subjective information. Accounting for such limitations complicates the mathematical modeling required to obtain realistic results in engineering analyses. The framework of imprecise probabilities provides a mathematical basis to deal with these problems which involve both probabilistic and non-probabilistic sources of uncertainty. A common feature of the various concepts of imprecise probabilities is the consideration of an entire set of probabilistic models in one analysis. But there are differences between the concepts in the mathematical description of this set and in the theoretical connection to the probabilistic models involved. This study is focused on fuzzy probabilities, which combine a probabilistic characterization of variability with a fuzzy characterization of imprecision. We discuss how fuzzy modeling can allow a more nuanced approach than interval-based concepts. The application in an engineering analysis is demonstrated by means of an example.
AB - Predicting the behavior and reliability of engineering structures and systems is often plagued by uncertainty and imprecision caused by sparse data, poor measurements and subjective information. Accounting for such limitations complicates the mathematical modeling required to obtain realistic results in engineering analyses. The framework of imprecise probabilities provides a mathematical basis to deal with these problems which involve both probabilistic and non-probabilistic sources of uncertainty. A common feature of the various concepts of imprecise probabilities is the consideration of an entire set of probabilistic models in one analysis. But there are differences between the concepts in the mathematical description of this set and in the theoretical connection to the probabilistic models involved. This study is focused on fuzzy probabilities, which combine a probabilistic characterization of variability with a fuzzy characterization of imprecision. We discuss how fuzzy modeling can allow a more nuanced approach than interval-based concepts. The application in an engineering analysis is demonstrated by means of an example.
UR - http://www.scopus.com/inward/record.url?scp=79958131012&partnerID=8YFLogxK
U2 - 10.1061/41170(400)7
DO - 10.1061/41170(400)7
M3 - Conference contribution
AN - SCOPUS:79958131012
SN - 9780784411704
T3 - Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management - Proceedings of the ICVRAM 2011 and ISUMA 2011 Conferences
SP - 53
EP - 61
BT - Vulnerability, Uncertainty, and Risk
T2 - International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2011 and the International Symposium on Uncertainty Modeling and Analysis, ISUMA 2011
Y2 - 11 April 2011 through 13 April 2011
ER -