Matches in SemOpenAlex for { <https://semopenalex.org/work/W2898890197> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2898890197 abstract "Statistical metamodels can robustly predict manufacturing process and engineering systems design results. Various techniques, such as Kriging, polynomial regression, artificial neural network and others, are each best suited for different scenarios that can range across a design space. Thus, methods are needed to identify the most appropriate metamodel or model composite for a given problem. To account for pros and cons of different metamodeling techniques for a wide diversity of data sets, in this paper we introduce a super-metamodel optimization framework (SMOF) to improve overall prediction accuracy by integrating different metamodeling techniques without a need for additional data. The SMOF defines an iterative process first to construct multiple metamodels using different methods and then aggregate them into a weighted composite and finally optimize the super-metamodel through advanced sampling. The optimized super-metamodel can reduce an overall prediction error and sustains the performance regardless of dataset variation. To verify the method, we apply it to 24 test problems representing various scenarios. A case study conducted with additive manufacturing process data shows method effectiveness in practice." @default.
- W2898890197 created "2018-11-09" @default.
- W2898890197 creator A5008825287 @default.
- W2898890197 creator A5020496465 @default.
- W2898890197 creator A5022023988 @default.
- W2898890197 creator A5038220921 @default.
- W2898890197 creator A5044388284 @default.
- W2898890197 date "2018-08-26" @default.
- W2898890197 modified "2023-09-27" @default.
- W2898890197 title "A Super-Metamodeling Framework to Optimize System Predictability" @default.
- W2898890197 cites W1495775210 @default.
- W2898890197 cites W1523989055 @default.
- W2898890197 cites W165037595 @default.
- W2898890197 cites W1698690719 @default.
- W2898890197 cites W2002016471 @default.
- W2898890197 cites W2002272403 @default.
- W2898890197 cites W2034374737 @default.
- W2898890197 cites W2038669746 @default.
- W2898890197 cites W2040870580 @default.
- W2898890197 cites W2048711666 @default.
- W2898890197 cites W2069350523 @default.
- W2898890197 cites W2078035571 @default.
- W2898890197 cites W2122363371 @default.
- W2898890197 cites W2143022286 @default.
- W2898890197 cites W2145475762 @default.
- W2898890197 cites W2151794096 @default.
- W2898890197 cites W2330604450 @default.
- W2898890197 cites W2487770199 @default.
- W2898890197 cites W2559924745 @default.
- W2898890197 cites W2620603478 @default.
- W2898890197 cites W2765136386 @default.
- W2898890197 cites W2765887078 @default.
- W2898890197 cites W2917134690 @default.
- W2898890197 doi "https://doi.org/10.1115/detc2018-86055" @default.
- W2898890197 hasPublicationYear "2018" @default.
- W2898890197 type Work @default.
- W2898890197 sameAs 2898890197 @default.
- W2898890197 citedByCount "4" @default.
- W2898890197 countsByYear W28988901972020 @default.
- W2898890197 countsByYear W28988901972021 @default.
- W2898890197 countsByYear W28988901972022 @default.
- W2898890197 crossrefType "proceedings-article" @default.
- W2898890197 hasAuthorship W2898890197A5008825287 @default.
- W2898890197 hasAuthorship W2898890197A5020496465 @default.
- W2898890197 hasAuthorship W2898890197A5022023988 @default.
- W2898890197 hasAuthorship W2898890197A5038220921 @default.
- W2898890197 hasAuthorship W2898890197A5044388284 @default.
- W2898890197 hasConcept C105795698 @default.
- W2898890197 hasConcept C111919701 @default.
- W2898890197 hasConcept C114614502 @default.
- W2898890197 hasConcept C119857082 @default.
- W2898890197 hasConcept C124101348 @default.
- W2898890197 hasConcept C154945302 @default.
- W2898890197 hasConcept C197640229 @default.
- W2898890197 hasConcept C199360897 @default.
- W2898890197 hasConcept C2780801425 @default.
- W2898890197 hasConcept C33923547 @default.
- W2898890197 hasConcept C41008148 @default.
- W2898890197 hasConcept C74193536 @default.
- W2898890197 hasConcept C81692654 @default.
- W2898890197 hasConcept C86610423 @default.
- W2898890197 hasConcept C98045186 @default.
- W2898890197 hasConceptScore W2898890197C105795698 @default.
- W2898890197 hasConceptScore W2898890197C111919701 @default.
- W2898890197 hasConceptScore W2898890197C114614502 @default.
- W2898890197 hasConceptScore W2898890197C119857082 @default.
- W2898890197 hasConceptScore W2898890197C124101348 @default.
- W2898890197 hasConceptScore W2898890197C154945302 @default.
- W2898890197 hasConceptScore W2898890197C197640229 @default.
- W2898890197 hasConceptScore W2898890197C199360897 @default.
- W2898890197 hasConceptScore W2898890197C2780801425 @default.
- W2898890197 hasConceptScore W2898890197C33923547 @default.
- W2898890197 hasConceptScore W2898890197C41008148 @default.
- W2898890197 hasConceptScore W2898890197C74193536 @default.
- W2898890197 hasConceptScore W2898890197C81692654 @default.
- W2898890197 hasConceptScore W2898890197C86610423 @default.
- W2898890197 hasConceptScore W2898890197C98045186 @default.
- W2898890197 hasLocation W28988901971 @default.
- W2898890197 hasOpenAccess W2898890197 @default.
- W2898890197 hasPrimaryLocation W28988901971 @default.
- W2898890197 hasRelatedWork W1525931652 @default.
- W2898890197 hasRelatedWork W2076301380 @default.
- W2898890197 hasRelatedWork W2104827390 @default.
- W2898890197 hasRelatedWork W2620550997 @default.
- W2898890197 hasRelatedWork W2773070730 @default.
- W2898890197 hasRelatedWork W2969571561 @default.
- W2898890197 hasRelatedWork W3121339476 @default.
- W2898890197 hasRelatedWork W3147153020 @default.
- W2898890197 hasRelatedWork W3150130873 @default.
- W2898890197 hasRelatedWork W4245715244 @default.
- W2898890197 isParatext "false" @default.
- W2898890197 isRetracted "false" @default.
- W2898890197 magId "2898890197" @default.
- W2898890197 workType "article" @default.