粒子群神经网络在手机物料库存预测中的应用

Particle swarm neural network application in the mobile phone material inventory forecast

物料库存预测是企业经营管理的重要方面,它直接影响企业的生产与销售以及企业经济效益的实现。开展物料安全库存预测研究对于合理地控制物料的进出,节约存货空间,降低库存成本,提高库存管理的科学性和企业经济效益具有重要的理论意义与实际应用价值。文章构建了基于粒子群优化的神经网络的手机物料库存预测模型,实验结果表明,手机物料库存的预测值与实际值吻合度较好,该方法可有效地提高预测准确度,对实际生产具有一定的指导作用。

Material stock prediction is an important aspect of enterprise management; it directly affects the enterprise production and sales as well as the realization of the enterprise economic benefit. Research on material safety stock forecast to reasonably control the materials in and out, saving inventory space, reduce the inventory cost, and raise the scientific nature of the inventory management and the enterprise economic benefit is of important theoretical significance and practical application value. In this paper, based on particle swarm optimization is constructed of mobile phone material stock prediction model of neural network, and the experimental results show that the predicted values and the actual value of mobile phone material inventory better alignment, this method can effectively improve the prediction accuracy, and is of certain guidance to the actual production.