Matches in SemOpenAlex for { <https://semopenalex.org/work/W1664778051> ?p ?o ?g. }
Showing items 1 to 65 of
65
with 100 items per page.
- W1664778051 abstract "Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network." @default.
- W1664778051 created "2016-06-24" @default.
- W1664778051 creator A5004065333 @default.
- W1664778051 creator A5022808200 @default.
- W1664778051 date "1993-06-01" @default.
- W1664778051 modified "2023-10-06" @default.
- W1664778051 title "LVQ and backpropagation neural networks applied to NASA SSME data" @default.
- W1664778051 cites W1593294636 @default.
- W1664778051 cites W1971735090 @default.
- W1664778051 cites W2081933362 @default.
- W1664778051 cites W2103496339 @default.
- W1664778051 cites W2470801339 @default.
- W1664778051 cites W3036512766 @default.
- W1664778051 hasPublicationYear "1993" @default.
- W1664778051 type Work @default.
- W1664778051 sameAs 1664778051 @default.
- W1664778051 citedByCount "0" @default.
- W1664778051 crossrefType "journal-article" @default.
- W1664778051 hasAuthorship W1664778051A5004065333 @default.
- W1664778051 hasAuthorship W1664778051A5022808200 @default.
- W1664778051 hasConcept C119857082 @default.
- W1664778051 hasConcept C153180895 @default.
- W1664778051 hasConcept C154945302 @default.
- W1664778051 hasConcept C155032097 @default.
- W1664778051 hasConcept C16910744 @default.
- W1664778051 hasConcept C199360897 @default.
- W1664778051 hasConcept C40567965 @default.
- W1664778051 hasConcept C41008148 @default.
- W1664778051 hasConcept C50644808 @default.
- W1664778051 hasConceptScore W1664778051C119857082 @default.
- W1664778051 hasConceptScore W1664778051C153180895 @default.
- W1664778051 hasConceptScore W1664778051C154945302 @default.
- W1664778051 hasConceptScore W1664778051C155032097 @default.
- W1664778051 hasConceptScore W1664778051C16910744 @default.
- W1664778051 hasConceptScore W1664778051C199360897 @default.
- W1664778051 hasConceptScore W1664778051C40567965 @default.
- W1664778051 hasConceptScore W1664778051C41008148 @default.
- W1664778051 hasConceptScore W1664778051C50644808 @default.
- W1664778051 hasLocation W16647780511 @default.
- W1664778051 hasOpenAccess W1664778051 @default.
- W1664778051 hasPrimaryLocation W16647780511 @default.
- W1664778051 hasRelatedWork W1509506313 @default.
- W1664778051 hasRelatedWork W1548957680 @default.
- W1664778051 hasRelatedWork W1560356501 @default.
- W1664778051 hasRelatedWork W1856772668 @default.
- W1664778051 hasRelatedWork W2022141188 @default.
- W1664778051 hasRelatedWork W2036374039 @default.
- W1664778051 hasRelatedWork W2100492357 @default.
- W1664778051 hasRelatedWork W2103219516 @default.
- W1664778051 hasRelatedWork W2122151167 @default.
- W1664778051 hasRelatedWork W2141416997 @default.
- W1664778051 hasRelatedWork W2143635295 @default.
- W1664778051 hasRelatedWork W2144762460 @default.
- W1664778051 hasRelatedWork W2162466100 @default.
- W1664778051 hasRelatedWork W2166960717 @default.
- W1664778051 hasRelatedWork W2186786274 @default.
- W1664778051 hasRelatedWork W2435669172 @default.
- W1664778051 hasRelatedWork W2787248463 @default.
- W1664778051 hasRelatedWork W3118973577 @default.
- W1664778051 hasRelatedWork W1857382257 @default.
- W1664778051 hasRelatedWork W1969487680 @default.
- W1664778051 isParatext "false" @default.
- W1664778051 isRetracted "false" @default.
- W1664778051 magId "1664778051" @default.
- W1664778051 workType "article" @default.