Details
| Original language | English |
|---|---|
| Pages | 756-759 |
| Number of pages | 4 |
| Publication status | Published - 1998 |
| Externally published | Yes |
| Event | 1998 International Computing Congress on Computing in Civil Engineering - Boston, MA, USA Duration: 18 Oct 1998 → 21 Oct 1998 |
Conference
| Conference | 1998 International Computing Congress on Computing in Civil Engineering |
|---|---|
| City | Boston, MA, USA |
| Period | 18 Oct 1998 → 21 Oct 1998 |
Abstract
Uncertain input parameters may result from `fuzziness', `randomness' or `fuzzy randomness'. With the use of fuzzy set theory, uncertain input parameters may be described mathematically as fuzzy variables or fuzzy random variables and may be integrated into safety assessment analysis. With the aid of α-discretization involving the multiple solution of special optimization problems, fuzzy input parameters are mapped onto the uncertain result set. If the deterministic input data are characterized by `fuzziness', the fuzzy results are uncertain outcomes of the structural analysis; safety assessment may then be carried out using possibility theory. If the input parameters exist in the form of fuzzy random variables, the computed fuzzy failure probabilities may be used for safety assessment. A fuzzy 1st-order reliability method (FFORM) is proposed, which is capable of handling fuzzy as well as fuzzy random variables.
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
- Computer Science(all)
- Computer Science Applications
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1998. 756-759 Paper presented at 1998 International Computing Congress on Computing in Civil Engineering, Boston, MA, USA.
Research output: Contribution to conference › Paper › Research › peer review
}
TY - CONF
T1 - Safety assessment using fuzzy theory
AU - Moeller, Bernd
AU - Beer, Michael
PY - 1998
Y1 - 1998
N2 - Uncertain input parameters may result from `fuzziness', `randomness' or `fuzzy randomness'. With the use of fuzzy set theory, uncertain input parameters may be described mathematically as fuzzy variables or fuzzy random variables and may be integrated into safety assessment analysis. With the aid of α-discretization involving the multiple solution of special optimization problems, fuzzy input parameters are mapped onto the uncertain result set. If the deterministic input data are characterized by `fuzziness', the fuzzy results are uncertain outcomes of the structural analysis; safety assessment may then be carried out using possibility theory. If the input parameters exist in the form of fuzzy random variables, the computed fuzzy failure probabilities may be used for safety assessment. A fuzzy 1st-order reliability method (FFORM) is proposed, which is capable of handling fuzzy as well as fuzzy random variables.
AB - Uncertain input parameters may result from `fuzziness', `randomness' or `fuzzy randomness'. With the use of fuzzy set theory, uncertain input parameters may be described mathematically as fuzzy variables or fuzzy random variables and may be integrated into safety assessment analysis. With the aid of α-discretization involving the multiple solution of special optimization problems, fuzzy input parameters are mapped onto the uncertain result set. If the deterministic input data are characterized by `fuzziness', the fuzzy results are uncertain outcomes of the structural analysis; safety assessment may then be carried out using possibility theory. If the input parameters exist in the form of fuzzy random variables, the computed fuzzy failure probabilities may be used for safety assessment. A fuzzy 1st-order reliability method (FFORM) is proposed, which is capable of handling fuzzy as well as fuzzy random variables.
UR - http://www.scopus.com/inward/record.url?scp=0031631581&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:0031631581
SP - 756
EP - 759
T2 - 1998 International Computing Congress on Computing in Civil Engineering
Y2 - 18 October 1998 through 21 October 1998
ER -