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https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/8927
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Soufi, Mohammed | - |
dc.contributor.author | Zahi, Abdelhadi | - |
dc.date.accessioned | 2024-12-09T09:20:03Z | - |
dc.date.available | 2024-12-09T09:20:03Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | https://dspace.univ-ghardaia.edu.dz/xmlui/handle/123456789/8927 | - |
dc.description.abstract | This 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.publisher | université Ghardaia | EN_en |
dc.subject | tunnel greenhouse; natural cooling; natural and forced ventilation; solar energy. | EN_en |
dc.subject | serre tunnel ; refroidissement naturel ; ventilation naturelle et forcée ; énergie solaire. | EN_en |
dc.title | Forecasting the 2022–2023 Indoor Greenhouse Temperature Using artificial Intelligence | EN_en |
dc.type | Thesis | EN_en |
Appears in Collections: | Mémoires de Master |
Files in This Item:
File | Description | Size | Format | |
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ilovepdf_merged - Moh Sof.pdf | 3.24 MB | Adobe PDF | View/Open |
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