摘要
当在对物流需求进行预测遇到较大波动的时间序列数据时,传统的以统计学为基础的预测方法在进行预测分析时误差会很大,本文建立了基于人工BP神经网络的预测方法并证明了其有效性。
When logistics demand forecast faces greater volatility in time series data,the traditional analytic method based on statistics will have a huge error when it is used for prediction.It creates a forecasts method based on artificial BP neural network and proves its effectiveness.
出处
《物流科技》
2007年第6期3-5,共3页
Logistics Sci-Tech
基金
广西科学基金资助项目(0640174)
关键词
物流需求
人工神经网络
时间序列
logistics amount
artificial neural network
time series
