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A Computational Method for Sensitivity Analysis under Uncertainty
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A Computational Method for Sensitivity Analysis under Uncertainty

作者:Wang, HC (Wang, Hongchun)[ 1 ]

编者:Yingying, S; Guiran, C; Zhen, L

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON LOGISTICS, ENGINEERING, MANAGEMENT AND COMPUTER SCIENCE (LEMCS 2015)

丛书: Advances in Intelligent Systems Research

卷: 117

页: 326-330

出版年: 2015
会议名称

会议: International Conference on Logistics Engineering, Management and Computer Science (LEMCS)

会议地点: Shenyang, PEOPLES R CHINA

会议日期: JUL 29-31, 2015

摘要

Sensitivity analysis (SA) is an important part in engineering design under the uncertainty to provide valuable information about the probabilistic characteristics of a response. In this paper, the variance-based methods and the cumulative distribution function (CDF)-based sensitivity coefficients were used in sensitivity analysis. The combination of sparse grid stochastic collocation (SC) and the generalized polynomial chaos (gPC) are proposed as a method to perform the sensitivity analysis. The computational method employs the gPC as a high-order representation for random quantities, a stochastic collocation (SC) approach to deal with complex/implicit response functions, and sparse grid to use a reduced set of samples. It can reduce the computational cost associated with uncertainty assessment without much sacrifice on the optimum solution. The effectiveness is demonstrated in two numerical examples.
关键词

作者关键词:Generalized Polynomial Chaos; Sensitivity Analysis; Stochastic Collocation; Sensitivity Coefficient; Uncertainty

KeyWords PlusIFFERENTIAL-EQUATIONS
作者信息

通讯作者地址: Wang, HC (通讯作者)
              Chongqing Normal Univ, Dept Math, Chongqing, Peoples R China.

地址:
              [ 1 ] Chongqing Normal Univ, Dept Math, Chongqing, Peoples R China

电子邮件地址:springwhch@126.com
出版商

ATLANTIS PRESS, 29 AVENUE LAVMIERE, PARIS, 75019, FRANCE
类别 / 分类

研究方向:Computer Science; Business & Economics; Operations Research & Management Science

Web of Science 类别:Computer Science, Artificial Intelligence; Management; Operations Research & Management Science
文献信息

文献类型roceedings Paper

语种:English

入藏号: WOS:000373107000063

ISBN:978-94-6252-102-5

ISSN: 1951-6851
其他信息

IDS 号: BE5OK

Web of Science 核心合集中的 "引用的参考文献": 11

Web of Science 核心合集中的 "被引频次": 0
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