摘要
随着电子技术的进步、世界经济一体化、全球化局面的出现,企业对知识和信息的有效管理已日益紧迫,可以说企业管理正进入新的理念。该文将改进的粒子群算法优化BP神经网络应用于库存管理系统中,建立库存预测模型为库存管理智能化提供辅助决策。从而使企业生产库存管理可以有效的对库存量进行控制,使库存量维持在一个比较合理的水平,将给企业带来巨大利益,因此对该方法的研究具有非常重要的现实意义。
Along with the fast development of economy,research based on enterprise competition ability has been the front field of man-agement science.This paper applied IPSOBP neural networks technology to demand forecast of inventory.Forecasting the amount of in-ventory passing this module can help the enterprise maintains a more reasonable raw material inventory quantity under the continue pro-ducing,and give asuggestion of raw material purchase.So the researches of thesis own academic creation and certain realistic meaning.
出处
《电脑知识与技术（过刊）》
2009年第6期1461-1463,共3页
Computer Knowledge and Technology
关键词
粒子群优化算法
神经网络
库存预测
Particle Swarm Optimization
Neural Network
Inventory Forecast
