The prediction of the behavior and reliability of engineering structures and systems is often plagued by uncertainty and imprecision caused by sparse data, poor measurements and linguistic 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 mathe-matical 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 engineering is demonstrated by means of two examples.
The paper is available in the following formats:
Michael Beer
Centre for Engineering Sustainability
School of Engineering
University of Liverpool
Liverpool
Mingqiang Zhang
Dept. of Civil & Environmental Engineering
BLK E1A #07-03
1 Engineering Drive 2
Singapore 117576
Ser Tong Quek
Dept. of Civil & Environmental Engineering
BLK E1A #07-03
1 Engineering Drive 2
Singapore 117576
Scott Ferson
100 North Country Road
Setauket, New York 11733
USA
| Michael Beer | cvebm@nus.edu.sg | |
| Mingqiang Zhang | mingqiang@nus.edu.sg | |
| Ser Tong Quek | cveqst@nus.edu.sg | |
| Scott Ferson | scott@ramas.com |
Send any remarks to isipta11@uibk.ac.at.