Matches in SemOpenAlex for { <https://semopenalex.org/work/W2073367419> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W2073367419 endingPage "4538" @default.
- W2073367419 startingPage "4528" @default.
- W2073367419 abstract "The main disadvantage of self-organizing polynomial neural networks (SOPNN) automatically structured and trained by the group method of data handling (GMDH) algorithm is a partial optimization of model weights as the GMDH algorithm optimizes only the weights of the topmost (output) node. In order to estimate to what extent the approximation accuracy of the obtained model can be improved the particle swarm optimization (PSO) has been used for the optimization of weights of all node-polynomials. Since the PSO is generally computationally expensive and time consuming a more efficient Levenberg–Marquardt (LM) algorithm is adapted for the optimization of the SOPNN. After it has been optimized by the LM algorithm the SOPNN outperformed the corresponding models based on artificial neural networks (ANN) and support vector method (SVM). The research is based on the meta-modeling of the thermodynamic effects in fluid flow measurements with time-constraints. The outstanding characteristics of the optimized SOPNN models are also demonstrated in learning the recurrence relations of multiple superimposed oscillations (MSO)." @default.
- W2073367419 created "2016-06-24" @default.
- W2073367419 creator A5066807113 @default.
- W2073367419 date "2013-09-01" @default.
- W2073367419 modified "2023-09-27" @default.
- W2073367419 title "Optimization of self-organizing polynomial neural networks" @default.
- W2073367419 cites W1980435942 @default.
- W2073367419 cites W2022175477 @default.
- W2073367419 cites W2030375269 @default.
- W2073367419 cites W2031645826 @default.
- W2073367419 cites W2051376043 @default.
- W2073367419 cites W2087070363 @default.
- W2073367419 cites W2139055047 @default.
- W2073367419 cites W2140247453 @default.
- W2073367419 cites W2147107577 @default.
- W2073367419 cites W2150913357 @default.
- W2073367419 cites W2162177192 @default.
- W2073367419 cites W2167383516 @default.
- W2073367419 cites W2256578114 @default.
- W2073367419 doi "https://doi.org/10.1016/j.eswa.2013.01.060" @default.
- W2073367419 hasPublicationYear "2013" @default.
- W2073367419 type Work @default.
- W2073367419 sameAs 2073367419 @default.
- W2073367419 citedByCount "13" @default.
- W2073367419 countsByYear W20733674192014 @default.
- W2073367419 countsByYear W20733674192016 @default.
- W2073367419 countsByYear W20733674192018 @default.
- W2073367419 countsByYear W20733674192020 @default.
- W2073367419 countsByYear W20733674192021 @default.
- W2073367419 crossrefType "journal-article" @default.
- W2073367419 hasAuthorship W2073367419A5066807113 @default.
- W2073367419 hasBestOaLocation W20733674192 @default.
- W2073367419 hasConcept C11413529 @default.
- W2073367419 hasConcept C119857082 @default.
- W2073367419 hasConcept C12267149 @default.
- W2073367419 hasConcept C126255220 @default.
- W2073367419 hasConcept C134306372 @default.
- W2073367419 hasConcept C13926793 @default.
- W2073367419 hasConcept C154945302 @default.
- W2073367419 hasConcept C33923547 @default.
- W2073367419 hasConcept C41008148 @default.
- W2073367419 hasConcept C50644808 @default.
- W2073367419 hasConcept C85617194 @default.
- W2073367419 hasConcept C90119067 @default.
- W2073367419 hasConceptScore W2073367419C11413529 @default.
- W2073367419 hasConceptScore W2073367419C119857082 @default.
- W2073367419 hasConceptScore W2073367419C12267149 @default.
- W2073367419 hasConceptScore W2073367419C126255220 @default.
- W2073367419 hasConceptScore W2073367419C134306372 @default.
- W2073367419 hasConceptScore W2073367419C13926793 @default.
- W2073367419 hasConceptScore W2073367419C154945302 @default.
- W2073367419 hasConceptScore W2073367419C33923547 @default.
- W2073367419 hasConceptScore W2073367419C41008148 @default.
- W2073367419 hasConceptScore W2073367419C50644808 @default.
- W2073367419 hasConceptScore W2073367419C85617194 @default.
- W2073367419 hasConceptScore W2073367419C90119067 @default.
- W2073367419 hasIssue "11" @default.
- W2073367419 hasLocation W20733674191 @default.
- W2073367419 hasLocation W20733674192 @default.
- W2073367419 hasOpenAccess W2073367419 @default.
- W2073367419 hasPrimaryLocation W20733674191 @default.
- W2073367419 hasRelatedWork W2033270444 @default.
- W2073367419 hasRelatedWork W2038479138 @default.
- W2073367419 hasRelatedWork W2143725017 @default.
- W2073367419 hasRelatedWork W2350832155 @default.
- W2073367419 hasRelatedWork W2350868219 @default.
- W2073367419 hasRelatedWork W2355927362 @default.
- W2073367419 hasRelatedWork W2977940867 @default.
- W2073367419 hasRelatedWork W3115048730 @default.
- W2073367419 hasRelatedWork W3196591613 @default.
- W2073367419 hasRelatedWork W4362499384 @default.
- W2073367419 hasVolume "40" @default.
- W2073367419 isParatext "false" @default.
- W2073367419 isRetracted "false" @default.
- W2073367419 magId "2073367419" @default.
- W2073367419 workType "article" @default.