|
|
【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ 感谢参与,应助指数 +1 cqwhch: 金币+20, ★★★★★最佳答案, 谢谢!!!!!!!! 2016-08-30 21:47:31 心静_依然: LS-EPI+1, 感谢应助 2016-08-30 22:28:44
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 Plus IFFERENTIAL-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 |
|