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- W2559264007 abstract "In this paper, we propose a novel variable setpoint RNN controller for maintaining comfortable indoor environment in double storey residential building by controlling the motorised thermostatic radiator valves (TRVs) mounted on radiators. In order to monitor the indoor environmental condition of the building the sensor interface collects information from different sensors and sends this information to random neural network (RNN) controller. The RNN controller ensures comfortable environment for occupants by regulating the air temperature of the building according to the setpoint suggested by PMV index based variable setpoint estimator. The proposed RNN controller is compared with ANN controller and it is found that accuracy of RNN controller is 26% more than ANN controller and conserves 2.75% more energy than ANN controller at PMV index based temperature setpoints. The RNN controller has the capability to adjust the room temperature to lower setpoints (not included in the training data) while ANN controller failed to maintain accurate comfortable environment for the operating points not covered in the training data. The results show that the percentage of accurate air temperature regulation for RNN controller is 95.69% while for ANN it is 2.22%." @default.
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- W2559264007 date "2014-03-06" @default.
- W2559264007 modified "2023-10-12" @default.
- W2559264007 title "Intelligent RNN Controller for domestic (residential) heating system" @default.
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