基于国际形势原材料价格波动下的供应链采购决策与分析  

Supply Chain Purchasing Decision and Analysis Based on the Fluctuation of Raw Material Prices in the International Situation

作　　者：王剑 

机构地区：[1]国网浙江省电力有限公司物资分公司,浙江 杭州

出　　处：《理论数学》2022年第12期2106-2113,共8页Pure Mathematics

摘　　要：在当前国际大宗原材料价格不断涨价的背景之下,电力设备采购成本不断增加,准确分析与预测物资采购趋势,有效支撑供应链采购决策,从而提升资源利用效率。为应对原材料价格上行的压力,电力企业以成品预测为核心目标,基于原料价格、社会经济因素、物资采购方面进行数据收集与清洗的基础上,创新采用基于多因素下金属价格预测和时空特征提取的金属价格组合预测方法,结合神经网络算法模型,搭建基于国际形式原材料价格波动下的供应链采购决策模型过程。该模型可操作性强、应用范围广、与时俱进,能够更好地满足电力企业的需求,为物资供应质效提升提供有力支撑。Under the background of the rising prices of international bulk raw materials, the procurement cost of power equipment is increasing. Accurate analysis and prediction of material procurement trends can effectively support supply chain procurement decisions, thereby improving resource utilization efficiency. In order to cope with the upward pressure on raw material prices, power companies take the forecast of finished products as the core goal, and on the basis of data collection and cleaning based on raw material prices, social and economic factors, and material procurement and innovatively adopt multi-factor metal price forecasting and spatiotemporal feature extraction. The combination forecasting method of metal price, combined with the neural network algorithm model, builds the supply chain procurement decision-making model process based on the fluctuation of international raw material prices. The model has strong operability, wide application range and keeps pace with the times, which can better meet the needs of power enterprises and provide strong support for the improvement of material supply quality and efficiency.

关 键 词：供应链采购 价格趋势预测 神经网络 

分 类 号：F274[经济管理—企业管理]