首页|Findings from Cadi Ayyad University Broaden Understanding of Machine Learning (P rediction of Residential Building Occupancy Using Machine Learning With Integrat ed Sensor and Survey Data: Insights From a Living Lab In Morocco)
Findings from Cadi Ayyad University Broaden Understanding of Machine Learning (P rediction of Residential Building Occupancy Using Machine Learning With Integrat ed Sensor and Survey Data: Insights From a Living Lab In Morocco)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning have be en published. According to news reporting originating from Marrakech, Morocco, b y NewsRx correspondents, research stated, “Building occupancy information is ess ential for effective energy management in buildings through the adoption of ener gy conservation and occupant-centric control strategies. These strategies endeav or to contribute to optimizing energy consumption while ensuring occupant comfor t.”Funders for this research include OCP Foundation, Ministry of Higher Education, Scientific Research and Innovation, Morocco.
MarrakechMoroccoAfricaBayesian Net worksCyborgsEmerging TechnologiesMachine LearningCadi Ayyad University
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