Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/67709
Type: Artigo de periódico
Title: Fuzzy arithmetic based on dimension-adaptive sparse grids: A case study of a large-scale finite element model under uncertain parameters
Author: Klimke, A
Nunes, RF
Wohlmuth, BI
Abstract: Fuzzy arithmetic provides a powerful tool to introduce uncertainty into mathematical models. With Zadeh's extension principle, one can obtain a fuzzy-valued extension of any real-valued objective function. An efficient and accurate approach to computing expensive multivariate functions of fuzzy numbers is given by fuzzy arithmetic based on sparse grids. In many cases, not all uncertain input parameters carry equal weight, or the objective model exhibits separable structure. These characteristics can be exploited by dimension-adaptive algorithms. As a result, the treatment of even higher-dimensional problems becomes possible. This is demonstrated in this paper by a case study involving two large-scale finite element models in vibration engineering that are subjected to fuzzy-valued input data.
Subject: fuzzy numbers
extension principle
computing fuzzy functions
uncertainty modeling
sparse grids
Country: Singapura
Editor: World Scientific Publ Co Pte Ltd
Rights: fechado
Identifier DOI: 10.1142/S0218488506004199
Date Issue: 2006
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
WOS000241502300003.pdf1.13 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.