Study On The Application Of BP Neural Network In The Prediction Of Office Building Energy Consumption

energy consumption is a big problem that can not be ignored in the development of the world. Energy consumption of building accounts for a large proportion of the total energy consumption. With the development of economy and the improvement of modernization, China's construction industry is in a stage of rapid development. Therefore, under the strong advocacy of China's energy conservation and emission reduction policy and sustainable development strategy, the construction industry must also follow this trend. In the future development, it is inevitable to integrate the environmental protection concept including economy, energy conservation and environmental protection. However, the energy-saving technology on buildings in China lags behind compared with developed countries, so based on the pattern of energy consumption on buildings in China, this paper proposes an application scheme of energy consumption prediction of an office building in South China by using BP neural network, in order to produce an available research direction for the prediction of energy consumption of office buildings, and promote it to other types of buildings, and provide relevant data support for building design. It will reduce the investigation cost of building energy consumption and be able to offer some reference for the relevant standards of controlling building energy consumption.