Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386014911> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W4386014911 endingPage "210" @default.
- W4386014911 startingPage "202" @default.
- W4386014911 abstract "Fire resistance analysis is a complex procedure. In this pursuit, engineers design experiments. However, fire tests are expensive and complex and require specialized equipment that is not accessible to many engineers. This further constrains the ability to test and advance fire research. In order to overcome the above challenges, this paper adopts novel machine learning to generate synthetic fire test data via Generative Adversarial Networks (GANs) from real fire tests to expand our knowledge database. Thus, with the addition of new tests, engineers will have access to a much larger pool of data that can help us to better analyze and design structures for fire. In addition, the availability of more data allows us to seriously integrate machine learning into the fire domain. Thus, this paper presents a new approach to expanding fire test data and applying regression and classification machine learning to predict the fire response of reinforced concrete columns. GANs provide an efficient way to generate synthetic data from real fire tests. Moreover, new data additions contribute to improving predictions of classification-based machine learning in comparison with regression-based machine learning." @default.
- W4386014911 created "2023-08-21" @default.
- W4386014911 creator A5047632598 @default.
- W4386014911 creator A5079406015 @default.
- W4386014911 date "2023-01-01" @default.
- W4386014911 modified "2023-10-02" @default.
- W4386014911 title "Fire Resistance Analysis Through Synthetic Fire Tests" @default.
- W4386014911 cites W1979690056 @default.
- W4386014911 cites W2045865816 @default.
- W4386014911 cites W2075575234 @default.
- W4386014911 cites W2168134915 @default.
- W4386014911 cites W2236328489 @default.
- W4386014911 cites W2565167788 @default.
- W4386014911 cites W2902802484 @default.
- W4386014911 cites W2923354478 @default.
- W4386014911 cites W2955869862 @default.
- W4386014911 cites W2956073690 @default.
- W4386014911 cites W2965462954 @default.
- W4386014911 cites W2983699080 @default.
- W4386014911 cites W3083483195 @default.
- W4386014911 cites W3102476541 @default.
- W4386014911 cites W3128298412 @default.
- W4386014911 cites W3207104538 @default.
- W4386014911 cites W3215109731 @default.
- W4386014911 doi "https://doi.org/10.1007/978-3-031-40395-8_14" @default.
- W4386014911 hasPublicationYear "2023" @default.
- W4386014911 type Work @default.
- W4386014911 citedByCount "0" @default.
- W4386014911 crossrefType "book-chapter" @default.
- W4386014911 hasAuthorship W4386014911A5047632598 @default.
- W4386014911 hasAuthorship W4386014911A5079406015 @default.
- W4386014911 hasConcept C115903868 @default.
- W4386014911 hasConcept C119857082 @default.
- W4386014911 hasConcept C134306372 @default.
- W4386014911 hasConcept C151730666 @default.
- W4386014911 hasConcept C154945302 @default.
- W4386014911 hasConcept C159985019 @default.
- W4386014911 hasConcept C16910744 @default.
- W4386014911 hasConcept C192562407 @default.
- W4386014911 hasConcept C2777267654 @default.
- W4386014911 hasConcept C2987912017 @default.
- W4386014911 hasConcept C33923547 @default.
- W4386014911 hasConcept C36503486 @default.
- W4386014911 hasConcept C37736160 @default.
- W4386014911 hasConcept C39890363 @default.
- W4386014911 hasConcept C41008148 @default.
- W4386014911 hasConcept C86803240 @default.
- W4386014911 hasConceptScore W4386014911C115903868 @default.
- W4386014911 hasConceptScore W4386014911C119857082 @default.
- W4386014911 hasConceptScore W4386014911C134306372 @default.
- W4386014911 hasConceptScore W4386014911C151730666 @default.
- W4386014911 hasConceptScore W4386014911C154945302 @default.
- W4386014911 hasConceptScore W4386014911C159985019 @default.
- W4386014911 hasConceptScore W4386014911C16910744 @default.
- W4386014911 hasConceptScore W4386014911C192562407 @default.
- W4386014911 hasConceptScore W4386014911C2777267654 @default.
- W4386014911 hasConceptScore W4386014911C2987912017 @default.
- W4386014911 hasConceptScore W4386014911C33923547 @default.
- W4386014911 hasConceptScore W4386014911C36503486 @default.
- W4386014911 hasConceptScore W4386014911C37736160 @default.
- W4386014911 hasConceptScore W4386014911C39890363 @default.
- W4386014911 hasConceptScore W4386014911C41008148 @default.
- W4386014911 hasConceptScore W4386014911C86803240 @default.
- W4386014911 hasLocation W43860149111 @default.
- W4386014911 hasOpenAccess W4386014911 @default.
- W4386014911 hasPrimaryLocation W43860149111 @default.
- W4386014911 hasRelatedWork W2901368259 @default.
- W4386014911 hasRelatedWork W2951939904 @default.
- W4386014911 hasRelatedWork W3046843850 @default.
- W4386014911 hasRelatedWork W3156291593 @default.
- W4386014911 hasRelatedWork W3198184493 @default.
- W4386014911 hasRelatedWork W4220812973 @default.
- W4386014911 hasRelatedWork W4221144885 @default.
- W4386014911 hasRelatedWork W4240838714 @default.
- W4386014911 hasRelatedWork W4293233653 @default.
- W4386014911 hasRelatedWork W4386716251 @default.
- W4386014911 isParatext "false" @default.
- W4386014911 isRetracted "false" @default.
- W4386014911 workType "book-chapter" @default.