基于大数据分析的电力物资采购需求预测模型研究  

Research on Demand Prediction Model for Power Material Procurement Based on Big Data Analysis

作　　者：徐任 XU Ren(Jintang Branch of Sichuan Hongye Electric Power Group,Chengdu,Sichuan,610000,China)

机构地区：[1]四川宏业电力集团金堂分公司,四川成都610000

出　　处：《智能城市应用》2025年第4期110-112,共3页Smart City Application

摘　　要：随着电力行业的快速发展,物资采购的科学性与前瞻性成为保障工程顺利实施的重要环节。传统的采购需求预测方法存在数据利用率低、响应滞后等问题,难以满足现代电力企业高效运作的需求。文中基于大数据分析技术,构建电力物资采购需求预测模型,从数据采集、特征处理到模型建立与优化,系统提升采购预测的准确性与时效性。研究结果显示,所构建模型能有效降低库存积压与采购成本,为电力企业实现智能供应链管理提供技术支撑。With the rapid development of the power industry,the scientific and forward-looking nature of material procurement has become an important link in ensuring the smooth implementation of projects.The traditional procurement demand prediction methods have problems such as low data utilization and delayed response,which are difficult to meet the efficient operation needs of modern power enterprises.Based on big data analysis technology,this article constructs a demand prediction model for power material procurement.From data collection and feature processing to model establishment and optimization,the system improves the accuracy and timeliness of procurement prediction.The research results show that the constructed model can effectively reduce inventory backlog and procurement costs,providing technical support for power enterprises to achieve intelligent supply chain management.

关 键 词：大数据分析 电力物资 采购管理 需求预测 数据建模 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]