{"title":"Research on Optimization Algorithm of Intelligent Connected Vehicle Recognition Based on Long Short-Term Memory Network","authors":"Moli Wang, Yandong Shen, Fei Gao, Qiao Song","doi":"10.1109/ICDSCA56264.2022.9988502","DOIUrl":null,"url":null,"abstract":"In recent years, intelligent driving has gradually entered the public's awareness due to the rapid and continuous development of the Internet information age. The most mature application of intelligent driving technology is currently the intelligently networked vehicle, which is capable of applying relevant knowledge in various fields in an extremely comprehensive manner and is being tested for the maturity of autonomous driving technology to a considerable extent. As intelligent networked vehicles have progressed, safety issues in autonomous driving have gradually attracted public attention and become a popular research area. This paper primarily discusses the related issues of intelligent networked vehicles in the context of executing automatic driving and focuses on the identification and optimization algorithms of such vehicles during operation. Additionally, a particle swarm algorithm optimizes the identification optimization process, and a long short-term memory network replaces the relevant characteristics to ensure its operation's reliability.","PeriodicalId":416983,"journal":{"name":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSCA56264.2022.9988502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, intelligent driving has gradually entered the public's awareness due to the rapid and continuous development of the Internet information age. The most mature application of intelligent driving technology is currently the intelligently networked vehicle, which is capable of applying relevant knowledge in various fields in an extremely comprehensive manner and is being tested for the maturity of autonomous driving technology to a considerable extent. As intelligent networked vehicles have progressed, safety issues in autonomous driving have gradually attracted public attention and become a popular research area. This paper primarily discusses the related issues of intelligent networked vehicles in the context of executing automatic driving and focuses on the identification and optimization algorithms of such vehicles during operation. Additionally, a particle swarm algorithm optimizes the identification optimization process, and a long short-term memory network replaces the relevant characteristics to ensure its operation's reliability.