Intelligent Prediction and Analysis System of Green Building Energy Consumption Based on BP_AdaBoost Algorithm

By predicting the future energy consumption of buildings, energy managers can judge the energy consumption trend of buildings in advance and implement energy procurement and energy regulation strategies in a planned way. It is the most basic work in building energy conservation projects. There are many methods to predict building energy consumption, including neural network method, software simulation method, gray system method, etc. This paper puts forward BP_AdaBoost algorithm (BPAA), studies and analyzes the IP and analysis system of green building(GB) energy consumption, and briefly introduces the classification of energy consumption prediction models and building design factors; Proposed BPAA, and analyzes the recognition process and steps of the algorithm. Finally, BP is established AdaBoost algorithm GB energy consumption IP model, through the comparative experiment with BP algorithm model, the results show that considering the overall effect, BP-The prediction effect of AdaBoost model is better than that of BP model. The BP proposed in this paper is verified- AdaBoost model has good prediction accuracy and convergence effect.