基于粗糙PSO-BP神经网络的冷链物流服务商选择研究

Research on the Selection of Service Providers for Cold Chain Logistics Based on the Rough PSO-BP Neural Network

首先,本文分析冷链物流市场现状及问题,并指出选取合适的冷链物流服务商对保障货物质量和客户满意度具有重要作用。其次,介绍BP神经网络和PSO算法的基本原理及其应用,并探讨基于粗糙集理论的特征选择方法。再次,基于粗糙PSO-BP神经网络的冷链物流服务商选择模型,本文详细介绍了模型的框架、流程和各个模块的实现方法。最后,本文进行实验设计和分析,评估了模型的性能,并与其他方法进行比较和讨论。实验结果表明,该模型在选取冷链物流服务商方面具有较高的准确性和预测能力。

Firstly,this paper analyses the current situation and problems of the cold chain logistics market,and points out that selecting a suitable service provider for cold chain logistics plays an important role in guaranteeing the quality of goods and customer satisfaction.Secondly,the basic principles of the BP neural network and PSO algorithm and their applications are introduced,and the feature selection method based on the rough set theory is discussed.Then,a selection model of service providers for cold chain logistics based on a rough PSO-BP neural network is proposed,and the framework,process,and implementation methods of each module of the model are introduced in detail.Finally,experimental design and analysis are conducted to evaluate the performance of the model and compare and discuss it with other methods.The experimental results show that the model has high accuracy and predictive capability in selecting service providers for cold chain logistics.