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• W3083195953 startingPage "1613" @default.
• W3083195953 abstract "This paper presents a design, simulation and performance evaluation of an optimized model for the Heating, Ventilation and Air-Conditioning (HVAC) systems using intelligent control algorithm. Fanger’s comfort method and genetic algorithms were used to obtain the optimal and initial values. The heat transmission coefficient between internal and external environments were determined depending on several inputs and factors acquired via supervisory control and data acquisition (SCADA) system sensors. The main feature of the real-time model is the prediction of the internal buildings environment, in order to control HVAC system for indoor environment and to utilize the optimum power consumed depending on optimized air temperature value. The predicted air temperature value and Predictive Mean Vote (PMV) value was applied using intelligent algorithm to obtain an optimal comfort level of the air temperature. The optimized air temperature value can be used in HVAC system controller to ensure that the temperature of indoor can reach a specific value after a known period of time. The use of genetic algorithm (GE) ensures that the used power is well below its peak value and maintains the comfort of the user’s environment." @default.
• W3083195953 created "2020-09-11" @default.
• W3083195953 creator A5031759332 @default.
• W3083195953 creator A5046473226 @default.
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• W3083195953 date "2020-12-01" @default.
• W3083195953 modified "2023-10-04" @default.
• W3083195953 title "Optimization of energy consumption and thermal comfort for intelligent building management system using genetic algorithm" @default.
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• W3083195953 doi "https://doi.org/10.11591/ijeecs.v20.i3.pp1613-1625" @default.
• W3083195953 hasPublicationYear "2020" @default.
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