Matches in SemOpenAlex for { <https://semopenalex.org/work/W2102300987> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W2102300987 endingPage "183" @default.
- W2102300987 startingPage "173" @default.
- W2102300987 abstract "This paper addresses the issue of performing global sensitivity analysis of model output with dependent inputs. First, we define variance-based sensitivity indices that allow for distinguishing the independent contributions of the inputs to the response variance from their mutual dependent contributions. Then, two sampling strategies are proposed for their non-parametric, numerical estimation. This approach allows us to estimate the sensitivity indices not only for individual inputs but also for groups of inputs. After testing the accuracy of the non-parametric method on some analytical test functions, the approach is employed to assess the importance of dependent inputs on a computer model for the migration of radioactive substances in the geosphere. We define a set of variance-based sensitivity indices for models with dependent inputs.The new sensitivity indices are those of the Rosenblatt transforms of the original variables.Non-parametric sampling-based strategies are proposed to compute the sensitivity indices.When input dependency is simply correlation, the simpler sampling procedure by Iman and Conover can be used.The proposed indices are computed and discussed for a radionuclide transport model a benchmark in sensitivity analysis." @default.
- W2102300987 created "2016-06-24" @default.
- W2102300987 creator A5011428350 @default.
- W2102300987 creator A5070503400 @default.
- W2102300987 creator A5089448558 @default.
- W2102300987 date "2015-10-01" @default.
- W2102300987 modified "2023-10-01" @default.
- W2102300987 title "Non-parametric methods for global sensitivity analysis of model output with dependent inputs" @default.
- W2102300987 cites W1968247170 @default.
- W2102300987 cites W1973823819 @default.
- W2102300987 cites W1979362125 @default.
- W2102300987 cites W1981618598 @default.
- W2102300987 cites W1994665973 @default.
- W2102300987 cites W1995565517 @default.
- W2102300987 cites W1998634089 @default.
- W2102300987 cites W2002661807 @default.
- W2102300987 cites W2009804339 @default.
- W2102300987 cites W2016133956 @default.
- W2102300987 cites W2016312558 @default.
- W2102300987 cites W2025175130 @default.
- W2102300987 cites W2026645785 @default.
- W2102300987 cites W2029767409 @default.
- W2102300987 cites W2033834417 @default.
- W2102300987 cites W2041619292 @default.
- W2102300987 cites W2053411831 @default.
- W2102300987 cites W2054740476 @default.
- W2102300987 cites W2063847981 @default.
- W2102300987 cites W2073344030 @default.
- W2102300987 cites W2087040335 @default.
- W2102300987 cites W2097441841 @default.
- W2102300987 cites W2101589741 @default.
- W2102300987 doi "https://doi.org/10.1016/j.envsoft.2015.07.010" @default.
- W2102300987 hasPublicationYear "2015" @default.
- W2102300987 type Work @default.
- W2102300987 sameAs 2102300987 @default.
- W2102300987 citedByCount "73" @default.
- W2102300987 countsByYear W21023009872016 @default.
- W2102300987 countsByYear W21023009872017 @default.
- W2102300987 countsByYear W21023009872018 @default.
- W2102300987 countsByYear W21023009872019 @default.
- W2102300987 countsByYear W21023009872020 @default.
- W2102300987 countsByYear W21023009872021 @default.
- W2102300987 countsByYear W21023009872022 @default.
- W2102300987 countsByYear W21023009872023 @default.
- W2102300987 crossrefType "journal-article" @default.
- W2102300987 hasAuthorship W2102300987A5011428350 @default.
- W2102300987 hasAuthorship W2102300987A5070503400 @default.
- W2102300987 hasAuthorship W2102300987A5089448558 @default.
- W2102300987 hasBestOaLocation W21023009872 @default.
- W2102300987 hasConcept C105795698 @default.
- W2102300987 hasConcept C117251300 @default.
- W2102300987 hasConcept C127413603 @default.
- W2102300987 hasConcept C149782125 @default.
- W2102300987 hasConcept C21200559 @default.
- W2102300987 hasConcept C24326235 @default.
- W2102300987 hasConcept C33923547 @default.
- W2102300987 hasConcept C39432304 @default.
- W2102300987 hasConcept C41008148 @default.
- W2102300987 hasConceptScore W2102300987C105795698 @default.
- W2102300987 hasConceptScore W2102300987C117251300 @default.
- W2102300987 hasConceptScore W2102300987C127413603 @default.
- W2102300987 hasConceptScore W2102300987C149782125 @default.
- W2102300987 hasConceptScore W2102300987C21200559 @default.
- W2102300987 hasConceptScore W2102300987C24326235 @default.
- W2102300987 hasConceptScore W2102300987C33923547 @default.
- W2102300987 hasConceptScore W2102300987C39432304 @default.
- W2102300987 hasConceptScore W2102300987C41008148 @default.
- W2102300987 hasFunder F4320320883 @default.
- W2102300987 hasLocation W21023009871 @default.
- W2102300987 hasLocation W21023009872 @default.
- W2102300987 hasLocation W21023009873 @default.
- W2102300987 hasLocation W21023009874 @default.
- W2102300987 hasOpenAccess W2102300987 @default.
- W2102300987 hasPrimaryLocation W21023009871 @default.
- W2102300987 hasRelatedWork W1529374794 @default.
- W2102300987 hasRelatedWork W1984686067 @default.
- W2102300987 hasRelatedWork W2025567228 @default.
- W2102300987 hasRelatedWork W2046837923 @default.
- W2102300987 hasRelatedWork W2065420425 @default.
- W2102300987 hasRelatedWork W2119158312 @default.
- W2102300987 hasRelatedWork W2294184591 @default.
- W2102300987 hasRelatedWork W2393503779 @default.
- W2102300987 hasRelatedWork W2552050053 @default.
- W2102300987 hasRelatedWork W2899084033 @default.
- W2102300987 hasVolume "72" @default.
- W2102300987 isParatext "false" @default.
- W2102300987 isRetracted "false" @default.
- W2102300987 magId "2102300987" @default.
- W2102300987 workType "article" @default.