Forecasting the 2022–2023 Indoor Greenhouse Temperature Using artificial Intelligence

dc.contributor.authorSoufi, Mohammed
dc.contributor.authorZahi, Abdelhadi
dc.date.accessioned2024-12-09T09:20:03Z
dc.date.available2024-12-09T09:20:03Z
dc.date.issued2024
dc.description.abstractThis research uses various named agricultural methods to modify the environment for plant growth. Ideally, crops will be produced in areas that do not require particularly favorable climatic and environmental conditions, but the temperature and relative humidity conditions are adjusted to be optimal. This research work aims to design and operate two tunnel greenhouses, which have been prepared to be capable of studying their thermal behavior with and without cooling systems. The first one, without cooling systems, will serve as a control greenhouse, while the second will be modified to test the effect of cooling systems and any reported modifications.EN_en
dc.identifier.urihttps://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/8927
dc.publisheruniversité GhardaiaEN_en
dc.subjecttunnel greenhouse; natural cooling; natural and forced ventilation; solar energy.EN_en
dc.subjectserre tunnel ; refroidissement naturel ; ventilation naturelle et forcée ; énergie solaire.EN_en
dc.titleForecasting the 2022–2023 Indoor Greenhouse Temperature Using artificial IntelligenceEN_en
dc.typeThesisEN_en

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