Energy Consumption Prediction Model of Public Buildings Based on PSO-RBF

Abstract

By analyzing thechange characteristics of energy consumption of public buildings in hot summer and cold winter zone, a building energy consumption prediction model based on RBF neural network is established. On this basis, particle swarm optimization is used to optimize our model, and the building energy consumption prediction model based on PSO-RBF is established. This paper applies large numbers of data to construct sample set, trains the prediction model before and after optimization by software, and appliesit to a typical energy consumption prediction example of public buildings. The results show that the building energy consumption prediction model based on PSO-RBF occupies preferable learning ability and predication performance, and achieves the energy consumption prediction of public building accurately.