Matches in SemOpenAlex for { <https://semopenalex.org/work/W2079089464> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2079089464 abstract "The use of confidence estimation techniques on neural networks outputs plays an important role when these mathematical models are applied in many practical applications. However, few of these techniques have the capability to deal with variable noise rate in the predictions over the domain, making the assumptions about the reliability of these outputs become not suitable with their real accuracy. In this paper an extension to the non-linear regression method to estimate prediction intervals for feed forward neural networks is presented. The main idea of this method is that residuals variance should be estimated in function of the input data and not as a constant. Thus, using clustering techniques, distinct estimates of the residuals variance are made and then used to obtain new prediction intervals. Proceeding in this manner, the experiments results show that this approach can lead to prediction intervals that better reflect the confidence level of the neural network outputs." @default.
- W2079089464 created "2016-06-24" @default.
- W2079089464 creator A5027610217 @default.
- W2079089464 creator A5060127840 @default.
- W2079089464 creator A5090517396 @default.
- W2079089464 date "2009-06-01" @default.
- W2079089464 modified "2023-09-27" @default.
- W2079089464 title "A method to estimate prediction intervals for artificial neural networks that is sensitive to the noise distribution in the outputs" @default.
- W2079089464 cites W1554663460 @default.
- W2079089464 cites W1597787061 @default.
- W2079089464 cites W1985579611 @default.
- W2079089464 cites W1998485739 @default.
- W2079089464 cites W2034544282 @default.
- W2079089464 cites W2038654054 @default.
- W2079089464 cites W2106644119 @default.
- W2079089464 cites W2107376597 @default.
- W2079089464 cites W2125336244 @default.
- W2079089464 cites W2134732652 @default.
- W2079089464 doi "https://doi.org/10.1109/ijcnn.2009.5178953" @default.
- W2079089464 hasPublicationYear "2009" @default.
- W2079089464 type Work @default.
- W2079089464 sameAs 2079089464 @default.
- W2079089464 citedByCount "2" @default.
- W2079089464 countsByYear W20790894642012 @default.
- W2079089464 countsByYear W20790894642017 @default.
- W2079089464 crossrefType "proceedings-article" @default.
- W2079089464 hasAuthorship W2079089464A5027610217 @default.
- W2079089464 hasAuthorship W2079089464A5060127840 @default.
- W2079089464 hasAuthorship W2079089464A5090517396 @default.
- W2079089464 hasConcept C103402496 @default.
- W2079089464 hasConcept C105795698 @default.
- W2079089464 hasConcept C11413529 @default.
- W2079089464 hasConcept C115961682 @default.
- W2079089464 hasConcept C119857082 @default.
- W2079089464 hasConcept C121332964 @default.
- W2079089464 hasConcept C121955636 @default.
- W2079089464 hasConcept C140529851 @default.
- W2079089464 hasConcept C144133560 @default.
- W2079089464 hasConcept C154945302 @default.
- W2079089464 hasConcept C163258240 @default.
- W2079089464 hasConcept C196083921 @default.
- W2079089464 hasConcept C33923547 @default.
- W2079089464 hasConcept C41008148 @default.
- W2079089464 hasConcept C43214815 @default.
- W2079089464 hasConcept C44249647 @default.
- W2079089464 hasConcept C50644808 @default.
- W2079089464 hasConcept C62520636 @default.
- W2079089464 hasConcept C73555534 @default.
- W2079089464 hasConcept C99498987 @default.
- W2079089464 hasConceptScore W2079089464C103402496 @default.
- W2079089464 hasConceptScore W2079089464C105795698 @default.
- W2079089464 hasConceptScore W2079089464C11413529 @default.
- W2079089464 hasConceptScore W2079089464C115961682 @default.
- W2079089464 hasConceptScore W2079089464C119857082 @default.
- W2079089464 hasConceptScore W2079089464C121332964 @default.
- W2079089464 hasConceptScore W2079089464C121955636 @default.
- W2079089464 hasConceptScore W2079089464C140529851 @default.
- W2079089464 hasConceptScore W2079089464C144133560 @default.
- W2079089464 hasConceptScore W2079089464C154945302 @default.
- W2079089464 hasConceptScore W2079089464C163258240 @default.
- W2079089464 hasConceptScore W2079089464C196083921 @default.
- W2079089464 hasConceptScore W2079089464C33923547 @default.
- W2079089464 hasConceptScore W2079089464C41008148 @default.
- W2079089464 hasConceptScore W2079089464C43214815 @default.
- W2079089464 hasConceptScore W2079089464C44249647 @default.
- W2079089464 hasConceptScore W2079089464C50644808 @default.
- W2079089464 hasConceptScore W2079089464C62520636 @default.
- W2079089464 hasConceptScore W2079089464C73555534 @default.
- W2079089464 hasConceptScore W2079089464C99498987 @default.
- W2079089464 hasLocation W20790894641 @default.
- W2079089464 hasOpenAccess W2079089464 @default.
- W2079089464 hasPrimaryLocation W20790894641 @default.
- W2079089464 hasRelatedWork W1551678009 @default.
- W2079089464 hasRelatedWork W1911571129 @default.
- W2079089464 hasRelatedWork W1994296101 @default.
- W2079089464 hasRelatedWork W1998522803 @default.
- W2079089464 hasRelatedWork W2006014102 @default.
- W2079089464 hasRelatedWork W2068737822 @default.
- W2079089464 hasRelatedWork W2098309673 @default.
- W2079089464 hasRelatedWork W2126222482 @default.
- W2079089464 hasRelatedWork W2134189088 @default.
- W2079089464 hasRelatedWork W2135998216 @default.
- W2079089464 hasRelatedWork W2143293245 @default.
- W2079089464 hasRelatedWork W2144254731 @default.
- W2079089464 hasRelatedWork W2160870368 @default.
- W2079089464 hasRelatedWork W2169170926 @default.
- W2079089464 hasRelatedWork W2185738933 @default.
- W2079089464 hasRelatedWork W2185755542 @default.
- W2079089464 hasRelatedWork W2206924023 @default.
- W2079089464 hasRelatedWork W2552063930 @default.
- W2079089464 hasRelatedWork W2982518913 @default.
- W2079089464 hasRelatedWork W1580884604 @default.
- W2079089464 isParatext "false" @default.
- W2079089464 isRetracted "false" @default.
- W2079089464 magId "2079089464" @default.
- W2079089464 workType "article" @default.