摘要
提出了一种基于BP神经网络的天然气负荷预测模型,模型中考虑了影响负荷变化的各种因素。采用Levenberg Marquardt优化方法,并利用VisualC++和Matlab软件进行计算机仿真,已用于实例。仿真结果表明该方法具有较好的准确性。
A BPneuralnetworkbased load forecasting model of natural gas is presented, and in this model all the factors that influence the natural gas load change are taken into account. LevenbergMarquardt arithmetic is adopted, and computer simulation is accomplished with Visual C++ and Matlab. The model is applied to practical examples, and the results prove that it has a very accurate feature.
出处
《煤气与热力》
2003年第6期331-332,336,共3页
Gas & Heat
基金
国家985学科建设项目(X03140)
211二期学科建设项目
