摘要
运用粒子群算法优化BP神经网络初始权值及阈值,用多个影响安全库存的指标及安全库存设置量对网络进行训练,以达到对煤机企业安全库存设置量预测的目的。经实际验证,效果良好。
Uses particle swarm algorithm to optimize BP neural network initial weights and threshold, the network is trained by using multiple impact safety stock index and safety stock setting, in order to achieve the coal mine machinery enterprises to set the amount of safety stock for the purpose of prediction. It is proved that the effect is good.
出处
《煤炭技术》
北大核心
2017年第10期305-307,共3页
Coal Technology
关键词
粒子群算法
BP神经网络
优化
安全库存
预测
particle swarm optimization
BP neural network
optimization
safety stock
prediction
