基于改进BP神经网络的水产品冷链物流需求预测研究——以浙江省为例

Research on cold chain logistics demand prediction of aquatic products based on improved BP Neural Network:a case study of Zhejiang Province

冷链物流作为新技术发展,在我国物流中的地位越来越重要。浙江省作为水产品产量大省,对于水产品冷链物流的需求旺盛,但发展却相对滞后,严重影响水产品行业发展以及水产品出口的质量。本文分析影响浙江省水产品冷链物流发展的关键因素及流通过程中存在损耗大、水产品冷链物流成本高、信息化程度不高等问题,通过对浙江省2003-2018年影响水产品冷链物流指标数据进行整理,建立基于需求的水产品冷链物流预测模型,采用主成分分析和BP神经网络组合法对2019-2023年浙江省水产品冷链物流需求量进行预测;实验结果显示,改进后的预测模型可以有效地预测浙江省的水产品冷链物流需求量。通过预测值,为相关部门提出一些建议,以期能为浙江省的冷链物流设施建设提供依据.

As a new technology development,cold chain logistics plays an important role in China's logistics.As a province with a large output of aquatic products,Zhejiang Province has a strong demand for cold chain logistics of aquatic products,but its development is relatively backward,which seriously affects the development of aquatic product industry and the quality of aquatic products export.This paper analyzes the key factors affecting the development of aquatic products cold chain logistics in Zhejiang Province and the problems in circulation process,such as large loss,high cost of aquatic products cold chain logistics and low degree of informatization.By sorting out the index data of aquatic products cold chain logistics in Zhejiang Province from 2003 to 2018,a forecasting model of aquatic products cold chain logistics based on demand is established.The combined method of principal component analysis and BP Neural Network is used to forecast the demand of aquatic products cold chain logistics in Zhejiang Province from 2019 to 2023.The experimental results show that the improved model can effectively predict the demand for cold chain logistics of aquatic products in Zhejiang Province.Through the predicted value,some suggestions are put forward for relevant departments in order to provide basis for the construction of cold chain logistics facilities in Zhejiang Province.