On fuzzy input data and the worst scenario method
Applications of Mathematics (2003)
- Volume: 48, Issue: 6, page 487-496
- ISSN: 0862-7940
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topChleboun, Jan. "On fuzzy input data and the worst scenario method." Applications of Mathematics 48.6 (2003): 487-496. <http://eudml.org/doc/33162>.
@article{Chleboun2003,
abstract = {In practice, input data entering a state problem are almost always uncertain to some extent. Thus it is natural to consider a set $\mathcal \{U\}_\{\mathrm \{a\}d\}$ of admissible input data instead of a fixed and unique input. The worst scenario method takes into account all states generated by $\mathcal \{U\}_\{\mathrm \{a\}d\}$ and maximizes a functional criterion reflecting a particular feature of the state solution, as local stress, displacement, or temperature, for instance. An increase in the criterion value indicates a deterioration in the featured quantity. The method takes all the elements of $\mathcal \{U\}_\{\mathrm \{a\}d\}$ as equally important though this can be unrealistic and can lead to too pessimistic conclusions. Often, however, additional information expressed through a membership function of $\mathcal \{U\}_\{\mathrm \{a\}d\}$ is available, i.e., $\mathcal \{U\}_\{\mathrm \{a\}d\}$ becomes a fuzzy set. In the article, infinite-dimensional $\mathcal \{U\}_\{\mathrm \{a\}d\}$ are considered, two ways of introducing fuzziness into $\mathcal \{U\}_\{\mathrm \{a\}d\}$ are suggested, and the worst scenario method operating on fuzzy admissible sets is proposed to obtain a fuzzy set of outputs.},
author = {Chleboun, Jan},
journal = {Applications of Mathematics},
keywords = {fuzzy sets; uncertainty; worst scenario method; fuzzy sets; uncertainty; worst scenario method},
language = {eng},
number = {6},
pages = {487-496},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {On fuzzy input data and the worst scenario method},
url = {http://eudml.org/doc/33162},
volume = {48},
year = {2003},
}
TY - JOUR
AU - Chleboun, Jan
TI - On fuzzy input data and the worst scenario method
JO - Applications of Mathematics
PY - 2003
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 48
IS - 6
SP - 487
EP - 496
AB - In practice, input data entering a state problem are almost always uncertain to some extent. Thus it is natural to consider a set $\mathcal {U}_{\mathrm {a}d}$ of admissible input data instead of a fixed and unique input. The worst scenario method takes into account all states generated by $\mathcal {U}_{\mathrm {a}d}$ and maximizes a functional criterion reflecting a particular feature of the state solution, as local stress, displacement, or temperature, for instance. An increase in the criterion value indicates a deterioration in the featured quantity. The method takes all the elements of $\mathcal {U}_{\mathrm {a}d}$ as equally important though this can be unrealistic and can lead to too pessimistic conclusions. Often, however, additional information expressed through a membership function of $\mathcal {U}_{\mathrm {a}d}$ is available, i.e., $\mathcal {U}_{\mathrm {a}d}$ becomes a fuzzy set. In the article, infinite-dimensional $\mathcal {U}_{\mathrm {a}d}$ are considered, two ways of introducing fuzziness into $\mathcal {U}_{\mathrm {a}d}$ are suggested, and the worst scenario method operating on fuzzy admissible sets is proposed to obtain a fuzzy set of outputs.
LA - eng
KW - fuzzy sets; uncertainty; worst scenario method; fuzzy sets; uncertainty; worst scenario method
UR - http://eudml.org/doc/33162
ER -
References
top- Convex Models of Uncertainties in Applied Mechanics, Studies in Applied Mechanics, Vol. 25, Elsevier, Amsterdam, 1990. (1990)
- Information Gap Decision Theory, Academic Press, San Diego, 2001. (2001) Zbl0985.91013MR1856675
- What are the random and fuzzy sets and how to use them for uncertainty modelling in engineering systems? In: Whys and Hows in Uncertainty Modelling, Probability, Fuzziness and Anti-Optimization, I. Elishakoff (ed.), Springer Verlag, Wien-New York, 1999, pp. 63–125. (1999) MR1763168
- 10.1007/BF02088988, Ingenieur-Archiv 11 (1940), 461–469. (1940) DOI10.1007/BF02088988
- On the accumulation of disturbances in linear systems with constant coefficients, Dokl. Akad. Nauk SSSR 51 (1940), 339–342. (Russian) (1940)
- 10.1016/S0362-546X(99)00274-6, Nonlinear Anal. Theory Methods Appl. 44 (2001), 375–388. (2001) Zbl1002.35041MR1817101DOI10.1016/S0362-546X(99)00274-6
- 10.1177/058310249002201001, Shock Vib. Dig. 22 (1990), 1. (1990) DOI10.1177/058310249002201001
- Whys and Hows in Uncertainty Modelling, Probability, Fuzziness and Anti-Optimization, CISM Courses and Lectures No. 338, I. Elishakoff (ed.), Springer Verlag, Wien, New York, 1999. (1999) MR1763168
- Stochastic Finite Elements: A Spectral Approach, Springer Verlag, Berlin, 1991. (1991) MR1083354
- Reliable solutions of problems in the deformation theory of plasticity with respect to uncertain material function, Appl. Math. 41 (1996), 447–466. (1996) MR1415251
- 10.1016/S0362-546X(96)00236-2, Nonlinear Anal. Theory Methods Appl. 30 (1997), 3879–3890, Proceedings of the WCNA-96. (1997) MR1602891DOI10.1016/S0362-546X(96)00236-2
- Uncertainty: Models and Measures, Proceedings of the International Workshop (Lambrecht, Germany, July 22–24, 1996), Mathematical Research, Vol. 99, H. G. Natke, Y. Ben-Haim (ed.), Akademie Verlag, Berlin, 1997. (1997) Zbl0868.00034MR1478000
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