基于AI技术的物流仓储园区库存需求和采购预测  

Inventory Demand Procurement Forecast for LogisticsWarehousing Park Based on AI technology

作　　者：钱昇 蒋晓华 丁宏琳 周巍 QIAN Sheng;JIANG Xiaohua;DING Honglin;ZHOU Wei(State Grid Jinhua Power Supply Company,Jinhua 321000,China)

机构地区：[1]国网浙江省电力有限公司金华供电公司,浙江金华321000

出　　处：《微型电脑应用》2023年第6期86-89,共4页Microcomputer Applications

摘　　要：针对智慧物流仓储园区库存需求信息分析能力滞后的问题,提出新型的需求预测方案,实现物流仓储园区库存需求分析,通过构建新型需求分析模型动态地实现消耗评估,提高物流仓储园区库存需求分析能力。通过公式输入需求信息能够直接将物流仓储园区库存需求采购预测结果输出,并构建改进型神经网络模型,该模型融合了遗传算法模型和神经网络算法模型,提高了采购预测评估精度。实验表明,研究所提方法的采购方案成本降低了5%以上,采购方案决策能力提高了10%以上。Aiming at the problem of lagging in inventory demand information analysis capabilities of smart logistics warehousing parks,a new demand forecasting scheme is proposed.By constructing a new demand analysis model,consumption evaluation is dynamically realized,and the inventory demand of logistics warehousing parks is increased.By inputting demand information,formulas can directly output the forecast results of inventory demand purchases in logistics warehousing parks.An improved neural network model is established by combining genetic algorithm model and neural network algorithm to improve the accuracy of procurement forecast evaluation.Tests show that the cost of the procurement plan proposed by the institute is reduced by more than 5%,and the decision-making ability of the procurement plan is improved by more than 10%.

关 键 词：AI技术 需求预测 需求分析模型 库存需求分析 神经网络模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]