Research on the Prediction of Energy-saving Potential of Traffic Tunnel Based on BP Neural Network

Accurate grasp of underground building environmental temperature and humidity cooling heating loads is the basis for energy-saving analysis, ventilation air conditioning system design operation control. In order to come up with a method that can quickly accurately predict potential power station traffic tunnel, this paper takes Xiangyou pumped storage tunnel as research object designs BP neural network model relative prediction respect main influencing factors. Comparing test data, it verified has high accuracy. At same time, was used calculate energy saving ventilation. The results showed error predicting in summer less than 2% winter 0.3%. This obtain simply accurately, so be developed direction favorable buildings.