Elements of uncertainty modeling

Chleboun, Jan

  • Programs and Algorithms of Numerical Mathematics, Publisher: Institute of Mathematics AS CR(Prague), page 42-57

Abstract

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The goal of this contribution is to introduce some approaches to uncertainty modeling in a way accessible to non-specialists. Elements of the Monte Carlo method, polynomial chaos method, Dempster-Shafer approach, fuzzy set theory, and the worst (case) scenario method are presented.

How to cite

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Chleboun, Jan. "Elements of uncertainty modeling." Programs and Algorithms of Numerical Mathematics. Prague: Institute of Mathematics AS CR, 2010. 42-57. <http://eudml.org/doc/271344>.

@inProceedings{Chleboun2010,
abstract = {The goal of this contribution is to introduce some approaches to uncertainty modeling in a way accessible to non-specialists. Elements of the Monte Carlo method, polynomial chaos method, Dempster-Shafer approach, fuzzy set theory, and the worst (case) scenario method are presented.},
author = {Chleboun, Jan},
booktitle = {Programs and Algorithms of Numerical Mathematics},
keywords = {uncertainty quantification; Monte Carlo method; polynomial chaos; Karhunen-Loeve expansion; worst scenario method; Dempster-Shafer evidence theory; fuzzy sets},
location = {Prague},
pages = {42-57},
publisher = {Institute of Mathematics AS CR},
title = {Elements of uncertainty modeling},
url = {http://eudml.org/doc/271344},
year = {2010},
}

TY - CLSWK
AU - Chleboun, Jan
TI - Elements of uncertainty modeling
T2 - Programs and Algorithms of Numerical Mathematics
PY - 2010
CY - Prague
PB - Institute of Mathematics AS CR
SP - 42
EP - 57
AB - The goal of this contribution is to introduce some approaches to uncertainty modeling in a way accessible to non-specialists. Elements of the Monte Carlo method, polynomial chaos method, Dempster-Shafer approach, fuzzy set theory, and the worst (case) scenario method are presented.
KW - uncertainty quantification; Monte Carlo method; polynomial chaos; Karhunen-Loeve expansion; worst scenario method; Dempster-Shafer evidence theory; fuzzy sets
UR - http://eudml.org/doc/271344
ER -

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