Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

摘要：

　　Building Energy forecasting plays an important role in energy management and plan.Using mind evolutionary algorithm to find the optimal network weights and threshold,to optimize the BP neural network,can overcome the problem of the BP neural network into a local minimum point.The optimized network is used for time series prediction,and the same month forecast,to get two predictive values.Then two kinds of predictive values are put into neural network,to get the final forecast value.The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

作者: Chen Song Wu Zhong-Cheng Lv Hong

作者单位: High Magnetic Field Laboratory,Chinese Academy of Sciences,Hefei,230031,China;University of Science High Magnetic Field Laboratory,Chinese Academy of Sciences,Hefei,230031,China College of Mechanical and Electrical Engineering,Anhui Jianzhu University,Hefei,230601,China

会议类型: 国际会议

会议名称: The 1st International Symposium on Application of Materials Science and Energy Materials (SAMSE 2017)

会议地点: 上海

会议语种:英文

页码: 1-7

在线出版日期: 2017-12-28（万方平台首次上网日期，不代表论文的发表时间）