A Prediction Approach on Energy Consumption for Public Buildings Using Mind Evolutionary Algorithm and BP Neural Network

This paper proposes a prediction approach on energy consumption for public buildings based on mind evolutionary algorithm and BP neural network. The actual real-time data of some layer in a public building can be obtained online by our implemented building monitoring system, then several key factors which affect building energy consumption can be analyzed and determined by correlation analysis method. By using the mind evolutionary algorithm, the ideal weight values and threshold values of BP neural network are calculated, which can solve its problems of low efficiency and slow convergence. Finally, the performance and effectiveness of the proposed forecasting model are demonstrated through a case study of a building energy consumption monitoring system from practical engineering.