摘要
介绍RBF神经网络技术,提出一种基于RBF神经网络的燃气月负荷预测模型,实例预测取得了较好效果。探讨了数据归一化参数对负荷预测精度的影响。
The radial basis function (RBF) neural network technology is introduced. A gas load forecasting model based on RBF neural network is proposed, and a good forecasting effect is achieved. The influence of data normalization parameters on load forecasting accuracy is discussed.
出处
《煤气与热力》
2013年第5期1-4,共4页
Gas & Heat
关键词
RBF神经网络
数据归一化
燃气负荷预测
radial basis function (RBF) neu- ral network
data normalization
gas load forecasting