以MATLAB神经网络预测城市燃气调峰用气量

根据城市燃气季节负荷变化的特点，应用人工神经网络理论，在MATLAB环境下开发了可反映燃气负荷周期性变化趋势，并包括各种不确定因素波动因素的燃气季节负荷预测模型。根据已知的燃气干线管道的输气值，即可确定燃气季节性调峰用气量，所建模型具有较高收敛速度和预测精度，且具较强适用性和灵活性，可为储气设施的设计与建造提供理论依据。

Seasonal Load of the City Gas Network Forecast Based upon the Artificial Neural Networks Toolboxes

The seasonal load of city gas networks is one of the most fundamental design parameters in the peak-shaving of the underground gas reservoirs. According to the specialty of gas load,a forecast model based on the artificial neural networks toolboxes has been formed. It can express both characteristics of increment trend of time series and fluctuation from indefinite factors. The results through actual example show that the built model is of better convergence on computation and forecast preciseness,better applicability and flexibility than those of other models.