首页|Research Data from University of Nottingham Update Understanding of Machine Lear ning (Optimal Hvac Setpoints for Energy Efficiency and Thermal Comfort In Chines e Residential Buildings)
Research Data from University of Nottingham Update Understanding of Machine Lear ning (Optimal Hvac Setpoints for Energy Efficiency and Thermal Comfort In Chines e Residential Buildings)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting from Nottingham, United Kin gdom, by NewsRx journalists, research stated, “The easiest way to improve energy efficiency and thermal comfort in existing buildings is to adjust setpoints. Ho wever, although Chinese standards regulated the heating and cooling setpoints fo r different climate zones in China, they lacked consideration for occupants’ the rmal comfort and ignored the ventilation setpoints.”
NottinghamUnited KingdomEuropeCybo rgsEmerging TechnologiesMachine LearningUniversity of Nottingham
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