{"title":"基于改进遗传算法的跨境电商物流智能监测预警系统的设计与实现","authors":"Fei Lei, Zicen Liao, Mingxiu Huang, Hui Tian","doi":"10.1117/12.3014648","DOIUrl":null,"url":null,"abstract":"The rapid development of the cross-border e-commerce market has led to an increase in logistics complexity, and intelligent monitoring and early warning systems are needed to meet the challenges. The objective of this study is to design and implement a cross-border e-commerce logistics monitoring and early warning system based on improved genetic algorithms to enhance the reliability of transportation quality. The system collects data related to cross-border e-commerce logistics transportation quality, analyzes and optimizes the improved genetic algorithm in one system, and uses the improved genetic algorithm for decision-making and planning. The system has a real-time monitoring function to discover potential transportation quality problems and conduct predictive analysis to identify the min advance for timely warning. The system can provide cross-border e-commerce enterprises with more efficient logistics and transportation quality management, reduce costs and improve customer satisfaction. It helps enterprises to cope with logistics challenges, provide more reliable services, and promote the continuous development and prosperity of cross-border e-commerce.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"58 1","pages":"129690W - 129690W-4"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and realization of cross-border e-commerce logistics intelligent monitoring and early warning system based on improved genetic algorithm\",\"authors\":\"Fei Lei, Zicen Liao, Mingxiu Huang, Hui Tian\",\"doi\":\"10.1117/12.3014648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid development of the cross-border e-commerce market has led to an increase in logistics complexity, and intelligent monitoring and early warning systems are needed to meet the challenges. The objective of this study is to design and implement a cross-border e-commerce logistics monitoring and early warning system based on improved genetic algorithms to enhance the reliability of transportation quality. The system collects data related to cross-border e-commerce logistics transportation quality, analyzes and optimizes the improved genetic algorithm in one system, and uses the improved genetic algorithm for decision-making and planning. The system has a real-time monitoring function to discover potential transportation quality problems and conduct predictive analysis to identify the min advance for timely warning. The system can provide cross-border e-commerce enterprises with more efficient logistics and transportation quality management, reduce costs and improve customer satisfaction. It helps enterprises to cope with logistics challenges, provide more reliable services, and promote the continuous development and prosperity of cross-border e-commerce.\",\"PeriodicalId\":516634,\"journal\":{\"name\":\"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)\",\"volume\":\"58 1\",\"pages\":\"129690W - 129690W-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.3014648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3014648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and realization of cross-border e-commerce logistics intelligent monitoring and early warning system based on improved genetic algorithm
The rapid development of the cross-border e-commerce market has led to an increase in logistics complexity, and intelligent monitoring and early warning systems are needed to meet the challenges. The objective of this study is to design and implement a cross-border e-commerce logistics monitoring and early warning system based on improved genetic algorithms to enhance the reliability of transportation quality. The system collects data related to cross-border e-commerce logistics transportation quality, analyzes and optimizes the improved genetic algorithm in one system, and uses the improved genetic algorithm for decision-making and planning. The system has a real-time monitoring function to discover potential transportation quality problems and conduct predictive analysis to identify the min advance for timely warning. The system can provide cross-border e-commerce enterprises with more efficient logistics and transportation quality management, reduce costs and improve customer satisfaction. It helps enterprises to cope with logistics challenges, provide more reliable services, and promote the continuous development and prosperity of cross-border e-commerce.