基于人工神经网络的产品安全库存预测方法

2010 International Conference of Information Science and Management Engineering Pub Date : 2010-08-07 DOI:10.1109/ISME.2010.190

Ping Zhao, Jingjing Liu

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引用次数: 6

摘要

在销售产品时，为了防止不确定性事件导致产品缺货，企业通常会储备一定数量的安全库存。安全库存的数量与库存成本直接相关。如何计算安全库存量，传统的直接用公式计算的方法有很多局限性。本文采用人工神经网络对安全库存量进行预测。实验结果表明，该方法具有较高的精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Product Safety Stock Prediction Method Based on Artificial Neural Network

When selling products, in order to prevent products stockout due to the uncertainty events, enterprises usually reserves a certain amount of safety stock. The amount of safety stock is directly related to inventory costs. How to calculate the amount of safety stock, the traditional method of using formulas to calculate directly has many limitations. This paper used artificial neural network to predict the amount of safety stock. The experimental result shows high accuracy.

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来源期刊

2010 International Conference of Information Science and Management Engineering

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