{"title":"AIS和其他电信系统中受损数据的重建:综述","authors":"Marta Szarmach, Ireneusz Czarnowski","doi":"10.26408/127.02","DOIUrl":null,"url":null,"abstract":": AIS (Automatic Identification System) is a telecommunication system created to enable ships to transmit information regarding their trajectories (such as their position, speed, course, etc.) to other ships and shore stations. With the use of AIS, collisions between ships can be avoided. Unfortunately, AIS suffers from some technical issues that lead to part of the transmitted data being damaged (incorrect or missing). This paper contains a review of machine learning based methods of reconstructing this damaged AIS data as well as examples of inspiration from other telecommunication systems for dealing with this kind of a problem. Finally, after analysing frameworks available in the relevant literature, a novel algorithm for AIS data reconstruction is briefly presented.","PeriodicalId":269306,"journal":{"name":"Scientific Journal of Gdynia Maritime University","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstructing Damaged Data in AIS and Other Telecommunications Systems: A Survey\",\"authors\":\"Marta Szarmach, Ireneusz Czarnowski\",\"doi\":\"10.26408/127.02\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": AIS (Automatic Identification System) is a telecommunication system created to enable ships to transmit information regarding their trajectories (such as their position, speed, course, etc.) to other ships and shore stations. With the use of AIS, collisions between ships can be avoided. Unfortunately, AIS suffers from some technical issues that lead to part of the transmitted data being damaged (incorrect or missing). This paper contains a review of machine learning based methods of reconstructing this damaged AIS data as well as examples of inspiration from other telecommunication systems for dealing with this kind of a problem. Finally, after analysing frameworks available in the relevant literature, a novel algorithm for AIS data reconstruction is briefly presented.\",\"PeriodicalId\":269306,\"journal\":{\"name\":\"Scientific Journal of Gdynia Maritime University\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Journal of Gdynia Maritime University\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26408/127.02\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Journal of Gdynia Maritime University","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26408/127.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reconstructing Damaged Data in AIS and Other Telecommunications Systems: A Survey
: AIS (Automatic Identification System) is a telecommunication system created to enable ships to transmit information regarding their trajectories (such as their position, speed, course, etc.) to other ships and shore stations. With the use of AIS, collisions between ships can be avoided. Unfortunately, AIS suffers from some technical issues that lead to part of the transmitted data being damaged (incorrect or missing). This paper contains a review of machine learning based methods of reconstructing this damaged AIS data as well as examples of inspiration from other telecommunication systems for dealing with this kind of a problem. Finally, after analysing frameworks available in the relevant literature, a novel algorithm for AIS data reconstruction is briefly presented.