In the actual process of forecasting, the credibility of the result of traditional urban space load density prediction method depends on a number of sample data. But, in the actual, collecting a complete feasible data is quite difficult. Therefore this paper puts forward a way which combines the group decision-making method of mixed language information and the BP neural network to forecast the city power load density. This way uses group decision-making method of mixed language information to get the score value of the economy, population, geographic environment in all urban district, then by...
