基于随机森林预测的手机多品类批量订货决策OA

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.