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Solar radiation prediction methods applied to improve greenhouse climate control

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dc.contributor.authorCoelho, João Paulo
dc.contributor.authorCunha, José Boaventura
dc.contributor.authorOliveira, Paulo de Moura
dc.date.accessioned2010-11-09T16:54:46Z
dc.date.available2010-11-09T16:54:46Z
dc.date.issued2001
dc.description.abstractIn this paper, deterministic and Artificial Neural Networks (ANNs)based techniques are applied to generate solar radiation forecast with the purpose of being incorporateed within a greenhouse predictive control strategy. These predictions are essential to estimate heat load flunctions in the greenhouse caused by high frequency solar radiation changes, and so to improve ventilation and heating computation requeriments for the greenhouse.
dc.identifier.citationCoelho, João; Cunha, José; Oliveira, Paulo (2001)- Solar radiation prediction methods applied to improve greenhouse climate control. In World Congress of Computers in Agriculture and Natural Resources. Iguaçu Falls, Brasil. p. 154-160
dc.identifier.urihttp://hdl.handle.net/10198/2773
dc.language.isoeng
dc.subjectTime series prediction
dc.subjectHorticulture
dc.subjectArtificial neural networks
dc.subjectLinear regression
dc.titleSolar radiation prediction methods applied to improve greenhouse climate controlpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceIguaçu Falls, Brasilpor
oaire.citation.endPage160por
oaire.citation.startPage154por
oaire.citation.titleWorld Congress of Computers in Agriculture and Natural Resourcespor
person.familyNameCoelho
person.givenNameJoão Paulo
person.identifierR-001-EXZ
person.identifier.ciencia-idD61E-A586-7D4A
person.identifier.orcid0000-0002-7616-1383
person.identifier.ridJ-6887-2013
person.identifier.scopus-author-id55137039300
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication2861f33b-b49a-421d-9bfa-92b4304d2668
relation.isAuthorOfPublication.latestForDiscovery2861f33b-b49a-421d-9bfa-92b4304d2668

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