电力系统保护与控制Issue(7)：15-22,8.
采用混合语言信息群决策的电力负荷密度预测法
Power load density prediction method of using group decision-making of mixed language information
摘要
Abstract
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 using BP neural network to train the score and the load density, after that utilizing the net to predict the load density of pending district. The result shows that not only the computation process can get rid of the problem which need large collection of specific indicators quantitative data but also the result is very good.关键词
混合语言信息群决策方法/城市电力负荷密度预测/BP神经网络/三大类指标/指标综合评分值Key words
group decision-making method of mixed language information/urban density of power load forecasting/BP neural network/three types of indicators/comprehensive score values of indicators分类
信息技术与安全科学引用本文复制引用
周胜瑜,周任军,李红英,康信文..采用混合语言信息群决策的电力负荷密度预测法[J].电力系统保护与控制,2014,(7):15-22,8.基金项目
国家自然科学基金资助(51277016)；湖南省高校创新平台开放基金项目(12K074)；湖南省研究生科研创新项目立项(CX2011B359)This work is supported by National Natural Science Foundation of China (No.51277016) （51277016）
