Hourly heating load prediction of radiant floor heating systems based on BP neural network

BP neural network is used to predict hourly heating load and it requires fewer parameters for establishing the model. With the field survey data in a lower energy consuming building in Dalian city, establishes a prediction model of hourly heating load based on BP neural network and makes some improvement on it. The results show that the improved BP neural network prediction model based on polynomial fitting can accurately predict hourly heating load for one unit in the next 24 hours, and the prediction error is about 5%.