基于神经网络模型的中储粮直属库粮食收购排队优化研究

Research on the Optimization of Grain Purchase Queue in the Directly Affiliated Warehouse of China Grain Reserves Corporation Based on Neural Network Model

摘要: 针对中储粮直属库在粮食收购过程中存在的排队问题，本文提出基于神经网络模型的排队优化方法，通过构建的模型对粮食收购排队进行训练、分析和预测，实现对排队流程的优化和资源的合理分配，提高粮食收购效率，减少排队等待时间，为粮食收购提供更科学、高效的排队管理方案。

Abstract: In response to the queuing problem in the grain procurement process of China Grain Reserves Corporation’s directly affiliated warehouses, this paper proposes a queuing optimization method based on neural network models. By constructing a model to train, analyze, and predict the grain procurement queue, the optimization of the queuing process and the rational allocation of resources are achieved, improving the efficiency of grain procurement, reducing waiting time in queues, and providing a more scientific and efficient queuing management solution for grain procurement.