摘要
以物流配送中心库存管理策略(R,S)中库存量预测的问题为研究对象,提出应用非参数回归方法对库存量进行拟合,用该方法与最小二乘法比较。并用非参数K邻近法则对库存量进行预测,丰富订货期制定方法。以某物流配送中心31天大米滞留库存量数据为例,研究结果表明,核回归模型拟合值较一元二次回归模型优异,得到较为理想的结果,实现通过统计模型客观地对物流配送中心库存信息智能化管理提供理论依据。
Focusing on the problem of inventory forecast of inventory control strategy in the Distribution center （R,S）, non-parametric regression method is applied to fit for the inventory, which is compared with the least squares method and non-parametric k neighboring rule is used to predict the inventory. Finally, the data of 31 days＇ rice storred in the distribution center are taken as an example. The result shows that the kernel rergression model is better than the quadratic regression model.
出处
《物流技术》
2009年第11期106-108,共3页
Logistics Technology
关键词
非参数回归
核回归
邻近法则
库存量
滞留期
non-parametric regression
kernel regression
k neighboring law
inventory
remaining period
