电子学报2009，Vol.37Issue(11)：2444-2447,4.
基于RBF神经网络的时间序列交叉供热负荷预报研究
Study of Heat Load Forecasting Based on RBF Neural Network and Time Series Crossover
摘要
Abstract
According to the characteristics of heat supply and the demands of energy-saving control, heat load forecasting based on RBF neural network and time series crossover is proposed. Firstly,field measured data are pretreated to generate the load series which is used to found forecasting model. Then autocorrelation method is applied to determine the dimensions of the input vectors of the RBF neural network. Meanwhile, the horizontal and vertical forecasting models based on RBF neural network are established respectively. Finally,the crossover weight coefficients of the horizontal and vertical forecasting models are calculated by using the least-squares method. And the time series crossover forecasting model is obtained. Through comparing the simulation results, the accuracy of crossover forecasting is superior to horizontal and vertical forecasting,and the real-time ability of RBF neural network crossover forecasting is also better than BP neural network crossover forecasting.关键词
供热过程/负荷预报/RBF神经网络/时间序列交叉Key words
heat supply/ load forecasting/ RBF neural network/ time series crossover分类
信息技术与安全科学引用本文复制引用
陈烈,张永明,齐维贵,邓盛川,李娟..基于RBF神经网络的时间序列交叉供热负荷预报研究[J].电子学报,2009,37(11):2444-2447,4.基金项目
国家"十一五"重点科技攻关项目(No.2006BAJ03A05) （No.2006BAJ03A05）
哈尔滨市科技创新人才研究专项资金(No.Rc2006XK007001) （No.Rc2006XK007001）
