| Titre : | Artificial Intelligence-based techniques for micro-climate modeling of an agricultural greenhouse |
| Auteurs : | Ala Eddine Brike, Auteur ; Megherbi Hassina, Directeur de thèse |
| Type de document : | Monographie imprimée |
| Editeur : | Université Mohamed Kheider, 2026 |
| Langues: | Anglais |
| Mots-clés: | Greenhouse Microclimate, Artificial Intelligence, Predictive Modelling, Robust Control, H-infinity Controller, Sustainable Agriculture, Arid Climate, Energy Efficiency, Heating and Cooling Loads, Biskra, Algeria. |
| Résumé : |
Greenhouse agriculture in arid and semi-arid regions, such as Biskra, Alge?ria, faces significant challenges due to extreme climatic conditions, leading to
high energy consumption for microclimate regulation. This thesis presents a framework for intelligent microclimate management to enhance sustainabil?ity and productivity. The core of this work is the development and validation of advanced Artificial Intelligence (AI) models for the predictive modelling of the internal greenhouse environment. These predictive models serve as the foundation for a sophisticated control system. A robust H-infinity con?troller is designed and implemented to ensure precise temperature regula?tion, demonstrating superior performance over traditional methods by ef?fectively handling system uncertainties and external disturbances. Further?more, the research conducts a thorough analysis of the heating and cooling energy requirements of greenhouse structures in the Biskra province, eval?uating the economic and environmental costs associated with conventional energy sources. This work investigates and proposes sustainable energy uti?lization models, with a focus on solar solutions, tailored to the specific needs of the region. The results demonstrate that AI-based predictive modelling provides a reliable and accurate model of greenhouse climates, and robust control ensures a stable climate against external conditions. Energy models are also studied and proposed in this work, and their effective management significantly reduces energy consumption while maintaining optimal growth conditions. This thesis contributes a simulation and data-driven solution and experimental validation that addresses the climate modelling, climate con?trol, and energy in greenhouse agriculture, offering a viable pathway towards energy-efficient and resilient greenhouse farming in challenging climates. |
| Type de document : | Thése doctorat |
Disponibilité (1)
| Cote | Support | Localisation | Statut | Emplacement | |
|---|---|---|---|---|---|
| Th/1450 | Thèse de doctorat | BIB.FAC.ST. | Empruntable | Magazin |
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