基于径向基函数网络的能源消费量预测模型  

Energy Consumption Prediction Model Based on Radial Basis Function Network

作　　者：孙廷容[1] 杨菊香[1] 张洪波[1] 黄强[1] 王功[1] 

机构地区：[1]西安理工大学水利水电学院

出　　处：《西安理工大学学报》2006年第2期163-166,共4页Journal of Xi'an University of Technology

基　　金：山西省科学技术发展计划项目(041091);西安市科技计划项目(HJ05001-4)

摘　　要：采用径向基函数（RBF）神经网络方法进行能源消费量预测,建立了基于RBF神经网络的能源消费量预测模型.以我国1978～1997年的实际数据作为学习样本,对网络进行训练,拟合效果良好;以1998～2002年的实际数据检验网络,预测精度较高.并通过实例与BP网络进行比较,表明RBF网络预测模型优于BP网络预测模型.Energy consumption prediction is made by the use of radial basis function （RBF） neural network method, and energy consumption prediction model based on RBF neural network is established. The RBF neural network is trained with the actual data of 1978--1997 as learning sample with a good fitting effect. The RBF neural network is tested with the actual data of 1998-2002 and have a high prediction precision. Via the comparision with Back Propagation network, the results show that the RBF neural network is better than BP neural network in accuracy and speed of training.

关 键 词：径向基函数 神经网络 能源消费量 预测 

分 类 号：N945.24[自然科学总论—系统科学]