Author(s)

Chang Liu

Corresponding Author

Chang Liu

ABSTRACT

Power load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating cost and improving social and economic benefits. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for large data is constructed.

KEYWORDS

Total Factor Productivity, Forestry Industry, Technical Efficiency Change