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

作　　者：李连[1] 孙聪[2] 苏涛[1] 

机构地区：[1]海军航空工程学院控制工程系,山东烟台264001 [2]海军航空工程学院研究生管理大队,山东烟台264001

出　　处：《计算机与现代化》2012年第8期179-182,186,共5页Computer and Modernization

摘　　要：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.

关 键 词：航材备件 需求预测 改进BP网络 

分 类 号：TP389.1[自动化与计算机技术—计算机系统结构] TP391.9[自动化与计算机技术—计算机科学与技术]