A. Kawalec, W. Komorniczak, J. Pietrasiński, W. Czarnecki
{"title":"多功能雷达任务排序中的数据融合技术","authors":"A. Kawalec, W. Komorniczak, J. Pietrasiński, W. Czarnecki","doi":"10.1109/MIKON.2006.4345138","DOIUrl":null,"url":null,"abstract":"The paper presents the problem of tasks ranking in multifunction radar resources management. The data fusion tasks ranking approach is discussed. The neural network, fuzzy inference system, hybrid fuzzy-neural and fuzzy-probabilistic ranking algorithms are presented. The information sources for tasking process have been selected and discussed. Evaluation of the performance of the ranking process is based on defined costs of removal/delay measures. The testing results are shown and discussed.","PeriodicalId":315003,"journal":{"name":"2006 International Conference on Microwaves, Radar & Wireless Communications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The Data Fusion Techniques for Tasks Ranking in Multifunction Radar\",\"authors\":\"A. Kawalec, W. Komorniczak, J. Pietrasiński, W. Czarnecki\",\"doi\":\"10.1109/MIKON.2006.4345138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents the problem of tasks ranking in multifunction radar resources management. The data fusion tasks ranking approach is discussed. The neural network, fuzzy inference system, hybrid fuzzy-neural and fuzzy-probabilistic ranking algorithms are presented. The information sources for tasking process have been selected and discussed. Evaluation of the performance of the ranking process is based on defined costs of removal/delay measures. The testing results are shown and discussed.\",\"PeriodicalId\":315003,\"journal\":{\"name\":\"2006 International Conference on Microwaves, Radar & Wireless Communications\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 International Conference on Microwaves, Radar & Wireless Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIKON.2006.4345138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 International Conference on Microwaves, Radar & Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIKON.2006.4345138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Data Fusion Techniques for Tasks Ranking in Multifunction Radar
The paper presents the problem of tasks ranking in multifunction radar resources management. The data fusion tasks ranking approach is discussed. The neural network, fuzzy inference system, hybrid fuzzy-neural and fuzzy-probabilistic ranking algorithms are presented. The information sources for tasking process have been selected and discussed. Evaluation of the performance of the ranking process is based on defined costs of removal/delay measures. The testing results are shown and discussed.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
