江西水利电力大学学报2026，Vol.45Issue(1)：80-87,8.
基于随机森林预测的手机多品类批量订货决策
Batch decision-making for mobile phone products based on Random Forest prediction
摘要
Abstract
The rise of data-driven technology brings about new solution to problems such as high inventory costs and low turnover rates caused by rapidly changing market demands.Based on the Random Forest prediction method within data-driv-en approaches,we conduct batch decision-making for mobile phone products.Leveraging big data analytics,we mined histor-ical sales data and influencing factors of mobile phone products,processed the data,and transformed sales data into demand data.By constructing a Random Forest regression decision model,we can predict future mobile phone demand.Simultane-ously,by analyzing the total costs and profits of various product combinations under the Economic Order Quantity model,we can determine the order quantity that maximizes profit.The value of this paper lies in using large-scale data to build a Ran-dom Forest regression prediction model and providing the optimal order quantity for profit maximization under given cost constraints based on the prediction results.关键词
手机产品/随机森林回归/销量预测/批量决策Key words
mobile phone products/Random Forest regression/sales prediction/batch decision-making分类
管理科学引用本文复制引用
易东波,王天奇,胡启帆..基于随机森林预测的手机多品类批量订货决策[J].江西水利电力大学学报,2026,45(1):80-87,8.基金项目
江西省高校人文社会科学研究项目(GL21117) （GL21117）
