基于BP神经网络模型的小批量物料需求预测研究  

Research on small batch material demand prediction based on BP neural network model

作　　者：王元聪 WANG Yuancong(Luoyang Polytechnic,Luoyang,Henan 471000,China)

机构地区：[1]洛阳职业技术学院,河南洛阳471000

出　　处：《计算机应用文摘》2025年第9期76-78,共3页

摘　　要：文章针对多品种、小批量生产模式下的物料需求预测展开研究。首先,筛选出重点关注的物料,并采用BP神经网络模型对其周需求量进行数据集训练和预测误差分析。研究结果表明,作为一种非线性预测方法,BP神经网络模型仅在个别预测点上可能出现较大误差,整体预测效果较好。因此,BP神经网络模型可用于小批量物料需求的有效预测。The article focuses on the research of material demand forecasting under the multi variety small batch production mode.Firstly,select the key materials of concern and use a BP neural network model to train the weekly demand on the dataset and analyze the prediction error.The research results indicate that the BP neural network model,as a nonlinear prediction method,may only have significant errors at individual prediction points,and the overall prediction performance is good.Therefore,the BP neural network model can be used for effective prediction of small batch material demand.

关 键 词：多品种小批量 物料需求预测 BP神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]