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冷链运输智能监控系统的设计与实现

Design and implementation of an intelligent monitoring system for cold chain transportation
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摘要 为推动冷链业务市场化运作,促进冷链物流的全面发展,确保冷链运输过程中物品的安全性和优化物流计划成为亟待解决的关键问题。因此,研发一款足够智能的冷链运输监控系统以满足客户对冷链运输的实时查询、动态监控和历史数据追溯的需求至关重要。本文设计并实现了一款冷链运输智能监控系统,采用前后端分离技术与MVC(model-view-controller,模型-视图-控制器)架构,前端使用Vue 3.0框架,后端使用基于Spring Boot框架的Spring Cloud微服务架构,算法部分采用Python语言实现。系统引入时间序列预测算法,并对ARIMA、LSTM、BiLSTM、Transformer和iTransformer 5种算法的性能和准确度进行了实验对比分析,最终集成了LSTM、ARIMA和iTransformer三种表现优异的算法供用户选择。该系统可利用历史数据预测不同地区未来1-3年的冷链月运量需求,助力企业优化物流规划,提升冷链运输的效率与可靠性。 To advance the marketization of cold chain logistics and promote its comprehensive development,ensuring the safety of goods during cold chain transportation and optimizing logistics planning are critical issues that need to be addressed.Therefore,developing a sufficiently intelligent cold chain transportation monitoring system to meet the demands for real-time querying,dynamic monitoring,and historical data tracing is crucial.This paper designs and implements an intelligent cold chain transportation monitoring system,employing a front-end and back-end separation architecture with the Model-View-Controller(MVC)framework.The front end is built using the Vue 3.0 framework,while the back end utilizes the Spring Boot framework with a Spring Cloud microservices architecture.The algorithmic component is implemented in Python.The system incorporates time series forecasting algorithms and conducts a comparative analysis of the performance and accuracy of five algorithms:ARIMA,LSTM,BiLSTM,Transformer,and iTransformer.Ultimately,it integrates the LSTM,ARIMA,and iTransformer algorithms,which have demonstrated superior performance.The system uses historical data to predict the cold chain monthly demand for different regions over the next one to three years,aiding enterprises in optimizing logistics planning and enhancing the efficiency and reliability of cold chain transportation.
作者 张文祺 徐圣凯 秦宗毅 王怿平 田晓璇 冀振燕 ZHANG Wenqi;XU Shengkai;QIN Zongyi;WANG Yiping;TIAN Xiaoxuan;JI Zhenyan(School of Software,Beijing Jiaotong University,Beijing 100081,China)
出处 《河北省科学院学报》 2025年第1期21-25,75,共6页 Journal of The Hebei Academy of Sciences
关键词 冷链运输 智能监控 时间序列预测 iTransformer Cold chain transportation Intelligent monitoring Time series forecasting iTransformer
作者简介 张文祺(2002-),女,湖北武汉人,硕士,主要研究方向为智慧交通;通信作者:冀振燕(1972-),女,河南襄县人,博士,教授,主要研究方向为人工智能,信息安全.
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