Matches in SemOpenAlex for { <https://semopenalex.org/work/W2019011816> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2019011816 endingPage "1205" @default.
- W2019011816 startingPage "1191" @default.
- W2019011816 abstract "Abstract A general method to obtain approximate solutions for the random response of non-linear systems subjected to both additive and multiplicative Gaussian white noises is presented. Starting from the concept of linearization, the proposed method of “Probabilistic Linearization” (PL) is based on the replacement of the Fokker–Planck equation of the original non-linear system with an equivalent one relative to a linear system subjected to additive excitation only. By means of the general scheme of the weighted residuals, the unknown coefficients of the equivalent system are determined. Assuming a Gaussian probability density function of the response process and by choosing the weighting functions in a suitable way, the equivalence of the proposed method, called “Gaussian Probabilistic Linearization” (GPL), with the “Gaussian Stochastic Linearization” (GSL) applied to the coefficients of the Ito differential rule is evidenced. In addition, the generalization of the proposed method, called “Generalized Gaussian Probabilistic Linearization” (GGPL), is presented. Numerical applications show as, varying the choice of the weighting functions, it is possible to obtain different linearizations, with a variable degree of accuracy. For the two examples considered, different suitable combinations of the weighting functions lead to different equivalent linear systems, all characterized by the exact solution in terms of variance." @default.
- W2019011816 created "2016-06-24" @default.
- W2019011816 creator A5023756743 @default.
- W2019011816 creator A5055006309 @default.
- W2019011816 date "2006-12-01" @default.
- W2019011816 modified "2023-09-27" @default.
- W2019011816 title "A probabilistic linearization method for non-linear systems subjected to additive and multiplicative excitations" @default.
- W2019011816 cites W1966390194 @default.
- W2019011816 cites W1991409545 @default.
- W2019011816 cites W1992566019 @default.
- W2019011816 cites W1998455280 @default.
- W2019011816 cites W1998821109 @default.
- W2019011816 cites W2014439416 @default.
- W2019011816 cites W2016066646 @default.
- W2019011816 cites W2025102609 @default.
- W2019011816 cites W2028697190 @default.
- W2019011816 cites W2032006621 @default.
- W2019011816 cites W2048407829 @default.
- W2019011816 cites W2055438589 @default.
- W2019011816 cites W2073200005 @default.
- W2019011816 cites W2083157765 @default.
- W2019011816 cites W2085320477 @default.
- W2019011816 cites W2090244466 @default.
- W2019011816 cites W2109219092 @default.
- W2019011816 cites W4231708121 @default.
- W2019011816 cites W990433057 @default.
- W2019011816 doi "https://doi.org/10.1016/j.ijnonlinmec.2006.12.002" @default.
- W2019011816 hasPublicationYear "2006" @default.
- W2019011816 type Work @default.
- W2019011816 sameAs 2019011816 @default.
- W2019011816 citedByCount "4" @default.
- W2019011816 countsByYear W20190118162014 @default.
- W2019011816 countsByYear W20190118162020 @default.
- W2019011816 countsByYear W20190118162021 @default.
- W2019011816 countsByYear W20190118162023 @default.
- W2019011816 crossrefType "journal-article" @default.
- W2019011816 hasAuthorship W2019011816A5023756743 @default.
- W2019011816 hasAuthorship W2019011816A5055006309 @default.
- W2019011816 hasConcept C105795698 @default.
- W2019011816 hasConcept C11210021 @default.
- W2019011816 hasConcept C121332964 @default.
- W2019011816 hasConcept C134306372 @default.
- W2019011816 hasConcept C158622935 @default.
- W2019011816 hasConcept C28826006 @default.
- W2019011816 hasConcept C33923547 @default.
- W2019011816 hasConcept C42747912 @default.
- W2019011816 hasConcept C49937458 @default.
- W2019011816 hasConcept C62520636 @default.
- W2019011816 hasConceptScore W2019011816C105795698 @default.
- W2019011816 hasConceptScore W2019011816C11210021 @default.
- W2019011816 hasConceptScore W2019011816C121332964 @default.
- W2019011816 hasConceptScore W2019011816C134306372 @default.
- W2019011816 hasConceptScore W2019011816C158622935 @default.
- W2019011816 hasConceptScore W2019011816C28826006 @default.
- W2019011816 hasConceptScore W2019011816C33923547 @default.
- W2019011816 hasConceptScore W2019011816C42747912 @default.
- W2019011816 hasConceptScore W2019011816C49937458 @default.
- W2019011816 hasConceptScore W2019011816C62520636 @default.
- W2019011816 hasIssue "10" @default.
- W2019011816 hasLocation W20190118161 @default.
- W2019011816 hasOpenAccess W2019011816 @default.
- W2019011816 hasPrimaryLocation W20190118161 @default.
- W2019011816 hasRelatedWork W147052086 @default.
- W2019011816 hasRelatedWork W1993024450 @default.
- W2019011816 hasRelatedWork W1996796035 @default.
- W2019011816 hasRelatedWork W2018682603 @default.
- W2019011816 hasRelatedWork W2019011816 @default.
- W2019011816 hasRelatedWork W2025793054 @default.
- W2019011816 hasRelatedWork W2037379902 @default.
- W2019011816 hasRelatedWork W2045447888 @default.
- W2019011816 hasRelatedWork W2091896560 @default.
- W2019011816 hasRelatedWork W2109645051 @default.
- W2019011816 hasVolume "41" @default.
- W2019011816 isParatext "false" @default.
- W2019011816 isRetracted "false" @default.
- W2019011816 magId "2019011816" @default.
- W2019011816 workType "article" @default.