FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912669475> ?p ?o ?g. }

• W2912669475 endingPage "285" @default.
• W2912669475 startingPage "277" @default.
• W2912669475 abstract "A non-intrusive sequence to sequence load disaggregation method based on deep delated convolution residual network is proposed in this work. Firstly, the original power data is normalized, and then the sliding window used to create the input for the residual network. The dilated convolution residual network model reduces the difficulty of network optimization and solves the problem of vanishing gradient. The residual learning can improve the depth of the network and the ability of extracting data features. The difficulty of learning long time series data is solved by increasing the receptive field and capturing more data through dilated convolution, which can improve the ability of processing samples with low usage. The sequence to sequence disaggregation method can improve the disaggregation efficiency. Simulation results using two data sets of real house measurements show that proposed model can get better disaggregation results than existing studies, especially for the disaggregation of electrical appliances with low usage." @default.
• W2912669475 created "2019-02-21" @default.
• W2912669475 creator A5026906414 @default.
• W2912669475 creator A5045380530 @default.
• W2912669475 creator A5055825030 @default.
• W2912669475 creator A5068557401 @default.
• W2912669475 creator A5073568638 @default.
• W2912669475 date "2019-05-01" @default.
• W2912669475 modified "2023-10-01" @default.
• W2912669475 title "Non-intrusive load disaggregation based on deep dilated residual network" @default.
• W2912669475 cites W1735866749 @default.
• W2912669475 cites W1969541079 @default.
• W2912669475 cites W1987077486 @default.
• W2912669475 cites W1988917187 @default.
• W2912669475 cites W1993297921 @default.
• W2912669475 cites W1993328790 @default.
• W2912669475 cites W2066525309 @default.
• W2912669475 cites W2088953431 @default.
• W2912669475 cites W2115712706 @default.
• W2912669475 cites W2123070597 @default.
• W2912669475 cites W2123910460 @default.
• W2912669475 cites W2133079185 @default.
• W2912669475 cites W2180975645 @default.
• W2912669475 cites W2232605275 @default.
• W2912669475 cites W2330456757 @default.
• W2912669475 cites W2338554958 @default.
• W2912669475 cites W2412782625 @default.
• W2912669475 cites W2754499592 @default.
• W2912669475 cites W2789937392 @default.
• W2912669475 cites W2805224140 @default.
• W2912669475 cites W2810202497 @default.
• W2912669475 cites W2884243640 @default.
• W2912669475 cites W2889509723 @default.
• W2912669475 cites W3103730413 @default.
• W2912669475 doi "https://doi.org/10.1016/j.epsr.2019.01.034" @default.
• W2912669475 hasPublicationYear "2019" @default.
• W2912669475 type Work @default.
• W2912669475 sameAs 2912669475 @default.
• W2912669475 citedByCount "71" @default.
• W2912669475 countsByYear W29126694752019 @default.
• W2912669475 countsByYear W29126694752020 @default.
• W2912669475 countsByYear W29126694752021 @default.
• W2912669475 countsByYear W29126694752022 @default.
• W2912669475 countsByYear W29126694752023 @default.
• W2912669475 crossrefType "journal-article" @default.
• W2912669475 hasAuthorship W2912669475A5026906414 @default.
• W2912669475 hasAuthorship W2912669475A5045380530 @default.
• W2912669475 hasAuthorship W2912669475A5055825030 @default.
• W2912669475 hasAuthorship W2912669475A5068557401 @default.
• W2912669475 hasAuthorship W2912669475A5073568638 @default.
• W2912669475 hasConcept C102392041 @default.
• W2912669475 hasConcept C108583219 @default.
• W2912669475 hasConcept C111919701 @default.
• W2912669475 hasConcept C11413529 @default.
• W2912669475 hasConcept C121332964 @default.
• W2912669475 hasConcept C153180895 @default.
• W2912669475 hasConcept C154945302 @default.
• W2912669475 hasConcept C155512373 @default.
• W2912669475 hasConcept C163258240 @default.
• W2912669475 hasConcept C2778112365 @default.
• W2912669475 hasConcept C2778751112 @default.
• W2912669475 hasConcept C41008148 @default.
• W2912669475 hasConcept C45347329 @default.
• W2912669475 hasConcept C50644808 @default.
• W2912669475 hasConcept C54355233 @default.
• W2912669475 hasConcept C62520636 @default.
• W2912669475 hasConcept C86803240 @default.
• W2912669475 hasConceptScore W2912669475C102392041 @default.
• W2912669475 hasConceptScore W2912669475C108583219 @default.
• W2912669475 hasConceptScore W2912669475C111919701 @default.
• W2912669475 hasConceptScore W2912669475C11413529 @default.
• W2912669475 hasConceptScore W2912669475C121332964 @default.
• W2912669475 hasConceptScore W2912669475C153180895 @default.
• W2912669475 hasConceptScore W2912669475C154945302 @default.
• W2912669475 hasConceptScore W2912669475C155512373 @default.
• W2912669475 hasConceptScore W2912669475C163258240 @default.
• W2912669475 hasConceptScore W2912669475C2778112365 @default.
• W2912669475 hasConceptScore W2912669475C2778751112 @default.
• W2912669475 hasConceptScore W2912669475C41008148 @default.
• W2912669475 hasConceptScore W2912669475C45347329 @default.
• W2912669475 hasConceptScore W2912669475C50644808 @default.
• W2912669475 hasConceptScore W2912669475C54355233 @default.
• W2912669475 hasConceptScore W2912669475C62520636 @default.
• W2912669475 hasConceptScore W2912669475C86803240 @default.
• W2912669475 hasFunder F4320321001 @default.
• W2912669475 hasLocation W29126694751 @default.
• W2912669475 hasOpenAccess W2912669475 @default.
• W2912669475 hasPrimaryLocation W29126694751 @default.
• W2912669475 hasRelatedWork W2733060750 @default.
• W2912669475 hasRelatedWork W2738221750 @default.
• W2912669475 hasRelatedWork W2766146978 @default.
• W2912669475 hasRelatedWork W2773120646 @default.
• W2912669475 hasRelatedWork W3099850646 @default.
• W2912669475 hasRelatedWork W3156786002 @default.
• W2912669475 hasRelatedWork W3177163058 @default.
• W2912669475 hasRelatedWork W4245792239 @default.
• W2912669475 hasRelatedWork W4312417841 @default.
• W2912669475 hasRelatedWork W3108696707 @default.

• next