改进BP网络在航材需求预测中的应用

Application of Improvable Back-propagation Network in Air Material Requirement Forecast

针对航材备件需求预测问题,在对影响航材备件需求量的多个因素进行分析研究的基础上,运用改进BP神经网络算法进行预测的仿真实验。实验结果表明,改进BP神经网络能够对积累的历史数据进行充分的应用,并且有较高的预测准确性。

To the question of air-material-requirement forecast, based on the analysis and study of a couple of factors which can affect the air material requirement, the paper tries to use the improvable back-propagation network to do the emulate experiment of forecast. The result shows that the improvable back-propagation network can do a good job in the application of the history data and can make an exact forecast.