Matches in SemOpenAlex for { <https://semopenalex.org/work/W4320013902> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W4320013902 endingPage "115" @default.
- W4320013902 startingPage "93" @default.
- W4320013902 abstract "AbstractVariable refrigerant flow (VRF) technologies, also known as variable volume refrigerant (VRV) systems, are taken into account as one of the most efficient, environmentally friendly, and economically viable alternatives for providing cooling and heating demands in the buildings. The increasing tendency towards using VRF technologies, in addition to the huge progress in the computer science, have led to using machine learning and artificial intelligence for design, optimization, and control of such systems with a fast upward trend. Taking these points into account, this chapter aims at giving an overview of artificial intelligence technologies and machine learning methods utilization for VRF systems. It is done by describing their application in design, optimization, and control of them.KeywordsComputer scienceMachine learningMulti-objective optimizationLiterature reviewVariable refrigerant flow (VRF) systems" @default.
- W4320013902 created "2023-02-11" @default.
- W4320013902 creator A5014310300 @default.
- W4320013902 creator A5017808700 @default.
- W4320013902 creator A5026679911 @default.
- W4320013902 creator A5042586114 @default.
- W4320013902 creator A5053111115 @default.
- W4320013902 creator A5083950599 @default.
- W4320013902 creator A5091241527 @default.
- W4320013902 date "2023-01-01" @default.
- W4320013902 modified "2023-10-11" @default.
- W4320013902 title "Application of Machine Learning and Artificial Intelligence in Design, Optimization, and Control of VRF Systems" @default.
- W4320013902 cites W1974531744 @default.
- W4320013902 cites W2055079390 @default.
- W4320013902 cites W2385733385 @default.
- W4320013902 cites W2402068981 @default.
- W4320013902 cites W2538405680 @default.
- W4320013902 cites W2538462186 @default.
- W4320013902 cites W2570259655 @default.
- W4320013902 cites W2594841701 @default.
- W4320013902 cites W2595996626 @default.
- W4320013902 cites W2606190899 @default.
- W4320013902 cites W2736537308 @default.
- W4320013902 cites W2745744410 @default.
- W4320013902 cites W2760193045 @default.
- W4320013902 cites W2766746569 @default.
- W4320013902 cites W2768545726 @default.
- W4320013902 cites W2793948265 @default.
- W4320013902 cites W2804601703 @default.
- W4320013902 cites W2810048786 @default.
- W4320013902 cites W2938814897 @default.
- W4320013902 cites W2955545965 @default.
- W4320013902 cites W2969466286 @default.
- W4320013902 cites W2986065329 @default.
- W4320013902 cites W2986717494 @default.
- W4320013902 cites W2999382295 @default.
- W4320013902 cites W3018554309 @default.
- W4320013902 cites W3035504170 @default.
- W4320013902 cites W3036143609 @default.
- W4320013902 cites W3040269440 @default.
- W4320013902 cites W3120620784 @default.
- W4320013902 cites W3123535982 @default.
- W4320013902 cites W3125196517 @default.
- W4320013902 cites W3175092132 @default.
- W4320013902 cites W3201204749 @default.
- W4320013902 cites W3210897159 @default.
- W4320013902 cites W3211086033 @default.
- W4320013902 doi "https://doi.org/10.1007/978-981-19-6833-4_5" @default.
- W4320013902 hasPublicationYear "2023" @default.
- W4320013902 type Work @default.
- W4320013902 citedByCount "0" @default.
- W4320013902 crossrefType "book-chapter" @default.
- W4320013902 hasAuthorship W4320013902A5014310300 @default.
- W4320013902 hasAuthorship W4320013902A5017808700 @default.
- W4320013902 hasAuthorship W4320013902A5026679911 @default.
- W4320013902 hasAuthorship W4320013902A5042586114 @default.
- W4320013902 hasAuthorship W4320013902A5053111115 @default.
- W4320013902 hasAuthorship W4320013902A5083950599 @default.
- W4320013902 hasAuthorship W4320013902A5091241527 @default.
- W4320013902 hasConcept C119857082 @default.
- W4320013902 hasConcept C127413603 @default.
- W4320013902 hasConcept C131097465 @default.
- W4320013902 hasConcept C133731056 @default.
- W4320013902 hasConcept C13736549 @default.
- W4320013902 hasConcept C154945302 @default.
- W4320013902 hasConcept C199499590 @default.
- W4320013902 hasConcept C2775924081 @default.
- W4320013902 hasConcept C41008148 @default.
- W4320013902 hasConcept C78519656 @default.
- W4320013902 hasConceptScore W4320013902C119857082 @default.
- W4320013902 hasConceptScore W4320013902C127413603 @default.
- W4320013902 hasConceptScore W4320013902C131097465 @default.
- W4320013902 hasConceptScore W4320013902C133731056 @default.
- W4320013902 hasConceptScore W4320013902C13736549 @default.
- W4320013902 hasConceptScore W4320013902C154945302 @default.
- W4320013902 hasConceptScore W4320013902C199499590 @default.
- W4320013902 hasConceptScore W4320013902C2775924081 @default.
- W4320013902 hasConceptScore W4320013902C41008148 @default.
- W4320013902 hasConceptScore W4320013902C78519656 @default.
- W4320013902 hasLocation W43200139021 @default.
- W4320013902 hasOpenAccess W4320013902 @default.
- W4320013902 hasPrimaryLocation W43200139021 @default.
- W4320013902 hasRelatedWork W2961085424 @default.
- W4320013902 hasRelatedWork W3046775127 @default.
- W4320013902 hasRelatedWork W3107474891 @default.
- W4320013902 hasRelatedWork W3170094116 @default.
- W4320013902 hasRelatedWork W3209574120 @default.
- W4320013902 hasRelatedWork W4205958290 @default.
- W4320013902 hasRelatedWork W4286629047 @default.
- W4320013902 hasRelatedWork W4306321456 @default.
- W4320013902 hasRelatedWork W4306674287 @default.
- W4320013902 hasRelatedWork W4224009465 @default.
- W4320013902 isParatext "false" @default.
- W4320013902 isRetracted "false" @default.
- W4320013902 workType "book-chapter" @default.