跳到内容
Assessing the reliability of complex models : mathematical and statistical foundations of verification, validation, and uncertainty quantification 预览资料
关闭预览资料
正在查...

Assessing the reliability of complex models : mathematical and statistical foundations of verification, validation, and uncertainty quantification

著者: National Research Council (U.S.). Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification.; National Research Council (U.S.). Board on Mathematical Sciences and Their Applications.; National Research Council (U.S.). Division on Engineering and Physical Sciences.
出版商: Washington, D.C. : National Academies Press, ©2012.
版本/格式:   电子图书 : 文献 : 英语查看所有的版本和格式
数据库:WorldCat
提要:
"Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality  再读一些...
评估:

(尚未评估) 0 附有评论 - 争取成为第一个。

主题
更多类似这样的

 

在线查找

在图书馆查找

&AllPage.SpinnerRetrieving; 正在查找有这资料的图书馆...

详细书目

类型/形式: Electronic books
附加的形体格式: Print version:
Assessing the reliability of complex models.
Washington : National Academies Press, 2012
(OCoLC)784035096
材料类型: 文献, 互联网资源
文件类型: 互联网资源, 计算机文档
所有的著者/提供者: National Research Council (U.S.). Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification.; National Research Council (U.S.). Board on Mathematical Sciences and Their Applications.; National Research Council (U.S.). Division on Engineering and Physical Sciences.
ISBN: 9780309256353 0309256356
OCLC号码: 798361535
描述: 1 online resource (xi, 131 p.) : ill. (some col.)
内容: Introduction --
Sources of uncertainty and error --
Verification --
Emulation, reduced-order modeling, and forward propagation --
Model validation and prediction --
Making decisions --
Next steps in practice, research, and education for verification, validation, and uncertainty quantification --
Appendixes.
责任: Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification ; Board on Mathematical Sciences and Their Applications ; Division on Engineering and Physical Sciences.
更多信息:

摘要:

"Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. [This report] discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners"--Publisher's description.

评论

用户提供的评论
正在获取GoodReads评论...
正在检索DOGObooks的评论

标签

争取是第一个!
确认申请

你可能已经申请过这份资料。如果还是想申请,请选确认。

链接数据


<http://www.worldcat.org/oclc/798361535>
library:oclcnum"798361535"
library:placeOfPublication
library:placeOfPublication
owl:sameAs<info:oclcnum/798361535>
rdf:typeschema:Book
schema:about
<http://id.worldcat.org/fast/1160835>
rdf:typeschema:Intangible
schema:name"Uncertainty--Mathematical models"@en
schema:name"Uncertainty--Mathematical models."@en
schema:about
schema:about
schema:about
schema:about
schema:about
schema:bookFormatschema:EBook
schema:contributor
<http://viaf.org/viaf/142087451>
rdf:typeschema:Organization
schema:name"National Research Council (U.S.). Division on Engineering and Physical Sciences."
schema:contributor
<http://viaf.org/viaf/255741861>
rdf:typeschema:Organization
schema:name"National Research Council (U.S.). Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification."
schema:contributor
<http://viaf.org/viaf/146773723>
rdf:typeschema:Organization
schema:name"National Research Council (U.S.). Board on Mathematical Sciences and Their Applications."
schema:copyrightYear"2012"
schema:datePublished"2012"
schema:description"Introduction -- Sources of uncertainty and error -- Verification -- Emulation, reduced-order modeling, and forward propagation -- Model validation and prediction -- Making decisions -- Next steps in practice, research, and education for verification, validation, and uncertainty quantification -- Appendixes."@en
schema:description""Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. [This report] discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners"--Publisher's description."@en
schema:exampleOfWork<http://worldcat.org/entity/work/id/1181631861>
schema:genre"Electronic books."@en
schema:inLanguage"en"
schema:name"Assessing the reliability of complex models mathematical and statistical foundations of verification, validation, and uncertainty quantification"@en
schema:numberOfPages"131"
schema:publisher
schema:url<http://www.nap.edu/catalog.php?record_id=13395>
schema:url<http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=476038>
schema:url<http://site.ebrary.com/id/10594220>
schema:url
schema:workExample

Content-negotiable representations

关闭窗口

请登入WorldCat 

没有张号吗?很容易就可以 建立免费的账号.