基于BP神经网络的电商企业库存需求预测
Inventory Demand Prediction for E-Commerce Enterprises Based on BP Neural Network
王丽惜1
作者信息
- 1. 福州英华职业学院,福建福州 350000
- 折叠
摘要
随着电子商务的迅猛发展,市场需求的不稳定性日益凸显,这使得很多企业难以准确设定库存量,容易导致大量库存资金被占用.要想降低库存成本,必须准确预测市场需求,并据此设定合理的库存.文章以H公司为例,利用反向传播(Back Propagation,BP)神经网络预测方法预测其产成品需求,使企业保持合理的库存,减少不必要的库存资金.
Abstract
With the rapid development of e-commerce,the instability of market demand is becoming increasingly prominent,which makes it difficult for many enterprises to accurately set inventory levels and easily lead to a large amount of inventory funds being occupied.To reduce inventory costs,it is necessary to accurately predict market demand and set reasonable inventory accordingly.The article takes H Company as an example and uses Back Propagation(BP)neural network prediction method to predict its demand for finished products,enabling the enterprise to maintain reasonable inventory and reduce unnecessary inventory funds.
关键词
反向传播(BP)神经网络/电商企业/库存需求预测Key words
Back Propagation(BP)neural network/e-commerce enterprises/inventory demand forecasting引用本文复制引用
出版年
2024
NETL
NSTL
万方数据