Matches in SemOpenAlex for { <https://semopenalex.org/work/W2911847527> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2911847527 endingPage "012023" @default.
- W2911847527 startingPage "012023" @default.
- W2911847527 abstract "With the advent of sustainable energy systems based on renewable energy sources (RES) and the development of a new generation of district heating systems (4GDH), it has become imperative for cogeneration and RES plant operators, as well as district heating (DH) operators, to apply new tools that lead to improvements in production planning, energy efficiency, and at the same time, reduce costs of heat generation. In recent years, machine learning (ML) methods used for the estimation and forecasting of energy demand have drawn considerable attention due to their advantage over linear and nonlinear programming models. In this context, the paper presents an artificial neural network (ANN) approach for the prediction of short-term heat load in a district heating system. The ANN model is trained with past heat load data, weather data and social behavior components. The predictive performance of the neural network model is measured by the mean absolute percentage error (MAPE) and the root mean square error (RMSE)." @default.
- W2911847527 created "2019-02-21" @default.
- W2911847527 creator A5039353457 @default.
- W2911847527 creator A5056546717 @default.
- W2911847527 date "2019-01-23" @default.
- W2911847527 modified "2023-10-17" @default.
- W2911847527 title "Short-term heat load forecasting in district heating systems using artificial neural networks" @default.
- W2911847527 cites W1595796962 @default.
- W2911847527 cites W1720804347 @default.
- W2911847527 cites W1964984358 @default.
- W2911847527 cites W1965396214 @default.
- W2911847527 cites W1983094890 @default.
- W2911847527 cites W2037485309 @default.
- W2911847527 cites W2055603026 @default.
- W2911847527 cites W2058729718 @default.
- W2911847527 cites W2128728535 @default.
- W2911847527 cites W2140990199 @default.
- W2911847527 cites W2338443192 @default.
- W2911847527 cites W2342247891 @default.
- W2911847527 cites W2426605366 @default.
- W2911847527 cites W2487967714 @default.
- W2911847527 cites W2529742705 @default.
- W2911847527 doi "https://doi.org/10.1088/1755-1315/214/1/012023" @default.
- W2911847527 hasPublicationYear "2019" @default.
- W2911847527 type Work @default.
- W2911847527 sameAs 2911847527 @default.
- W2911847527 citedByCount "2" @default.
- W2911847527 countsByYear W29118475272021 @default.
- W2911847527 crossrefType "journal-article" @default.
- W2911847527 hasAuthorship W2911847527A5039353457 @default.
- W2911847527 hasAuthorship W2911847527A5056546717 @default.
- W2911847527 hasBestOaLocation W29118475271 @default.
- W2911847527 hasConcept C105795698 @default.
- W2911847527 hasConcept C119599485 @default.
- W2911847527 hasConcept C119857082 @default.
- W2911847527 hasConcept C121332964 @default.
- W2911847527 hasConcept C127413603 @default.
- W2911847527 hasConcept C139945424 @default.
- W2911847527 hasConcept C150217764 @default.
- W2911847527 hasConcept C163258240 @default.
- W2911847527 hasConcept C166957645 @default.
- W2911847527 hasConcept C188573790 @default.
- W2911847527 hasConcept C205649164 @default.
- W2911847527 hasConcept C2776756539 @default.
- W2911847527 hasConcept C2779343474 @default.
- W2911847527 hasConcept C33923547 @default.
- W2911847527 hasConcept C41008148 @default.
- W2911847527 hasConcept C423512 @default.
- W2911847527 hasConcept C50644808 @default.
- W2911847527 hasConcept C61797465 @default.
- W2911847527 hasConcept C62520636 @default.
- W2911847527 hasConceptScore W2911847527C105795698 @default.
- W2911847527 hasConceptScore W2911847527C119599485 @default.
- W2911847527 hasConceptScore W2911847527C119857082 @default.
- W2911847527 hasConceptScore W2911847527C121332964 @default.
- W2911847527 hasConceptScore W2911847527C127413603 @default.
- W2911847527 hasConceptScore W2911847527C139945424 @default.
- W2911847527 hasConceptScore W2911847527C150217764 @default.
- W2911847527 hasConceptScore W2911847527C163258240 @default.
- W2911847527 hasConceptScore W2911847527C166957645 @default.
- W2911847527 hasConceptScore W2911847527C188573790 @default.
- W2911847527 hasConceptScore W2911847527C205649164 @default.
- W2911847527 hasConceptScore W2911847527C2776756539 @default.
- W2911847527 hasConceptScore W2911847527C2779343474 @default.
- W2911847527 hasConceptScore W2911847527C33923547 @default.
- W2911847527 hasConceptScore W2911847527C41008148 @default.
- W2911847527 hasConceptScore W2911847527C423512 @default.
- W2911847527 hasConceptScore W2911847527C50644808 @default.
- W2911847527 hasConceptScore W2911847527C61797465 @default.
- W2911847527 hasConceptScore W2911847527C62520636 @default.
- W2911847527 hasLocation W29118475271 @default.
- W2911847527 hasOpenAccess W2911847527 @default.
- W2911847527 hasPrimaryLocation W29118475271 @default.
- W2911847527 hasRelatedWork W2594589062 @default.
- W2911847527 hasRelatedWork W2726592933 @default.
- W2911847527 hasRelatedWork W2778123278 @default.
- W2911847527 hasRelatedWork W2807954395 @default.
- W2911847527 hasRelatedWork W2942773263 @default.
- W2911847527 hasRelatedWork W3173604411 @default.
- W2911847527 hasRelatedWork W3216603269 @default.
- W2911847527 hasRelatedWork W4200265123 @default.
- W2911847527 hasRelatedWork W4213016846 @default.
- W2911847527 hasRelatedWork W4281693556 @default.
- W2911847527 hasVolume "214" @default.
- W2911847527 isParatext "false" @default.
- W2911847527 isRetracted "false" @default.
- W2911847527 magId "2911847527" @default.
- W2911847527 workType "article" @default.