华东交通大学学报Issue(2)：123-128,6.
BP神经网络在解决电力消耗问题中的应用
Application of BP Neural Network in Reducing Power Consumption
傅军栋 1喻勇 1黎丹1
作者信息
- 1. 华东交通大学电气与电子工程学院，江西 南昌 330013
- 折叠
摘要
Abstract
The BP neural network has great advantages in solving nonlinear complex system. This paper, using the population, economy and power consumption data during 1991-2011 in Jiangxi province as the research object, builds up electricity consumption forecasting models based on BP neural network. Model 1 adopts the annual popu⁃lation, economy and power consumption data during 1991-2009 as training samples, with those of 2010-2011 as test samples to verify the accuracy of the network. Then according to the historical data, it forecasts the power con⁃sumption based on factors of population and economy. Model 2 determines the multiple linear regression for non⁃linear multivariable functions through the regression analysis method, predicting electricity consumption through the parameters of the regression model. Results show Model 1 has good convergence with small prediction absolute error while Model 2 with the traditional method has larger errors. It proves that BP neural network is feasible in forecasting electric power consumption.关键词
BP神经网络/多元线性回归/最小二乘原理/电力预测Key words
BP neural network/multiple linear regression/least square method/power forecasting分类
信息技术与安全科学引用本文复制引用
傅军栋,喻勇,黎丹..BP神经网络在解决电力消耗问题中的应用[J].华东交通大学学报,2015,(2):123-128,6.
