{"title":"基于模糊测度理论的多传感器决策融合策略","authors":"Jung‐Min Yang, Jong-Hwan Kim","doi":"10.1109/ISIC.1995.525053","DOIUrl":null,"url":null,"abstract":"A multisensor decision fusion strategy with fuzzy measure theory is proposed. This fusion strategy is constructed for finding optimal decisions through fusing decisions derived from a suite of parallel sensors. Each element of the possible target object set is assigned a priori a fuzzy measure for all the sensors meaning the subjective weights of the sensors on each object. Through recursive sensing process all the possible target objects have the cumulative decision measures (CDM), which are derived from fuzzy measures to represent possibilities that one object is the target to be identified. The properties and applicability of the proposed algorithm is analyzed.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multisensor decision fusion strategy using fuzzy measure theory\",\"authors\":\"Jung‐Min Yang, Jong-Hwan Kim\",\"doi\":\"10.1109/ISIC.1995.525053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multisensor decision fusion strategy with fuzzy measure theory is proposed. This fusion strategy is constructed for finding optimal decisions through fusing decisions derived from a suite of parallel sensors. Each element of the possible target object set is assigned a priori a fuzzy measure for all the sensors meaning the subjective weights of the sensors on each object. Through recursive sensing process all the possible target objects have the cumulative decision measures (CDM), which are derived from fuzzy measures to represent possibilities that one object is the target to be identified. The properties and applicability of the proposed algorithm is analyzed.\",\"PeriodicalId\":219623,\"journal\":{\"name\":\"Proceedings of Tenth International Symposium on Intelligent Control\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Tenth International Symposium on Intelligent Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.1995.525053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Tenth International Symposium on Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.1995.525053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A multisensor decision fusion strategy using fuzzy measure theory
A multisensor decision fusion strategy with fuzzy measure theory is proposed. This fusion strategy is constructed for finding optimal decisions through fusing decisions derived from a suite of parallel sensors. Each element of the possible target object set is assigned a priori a fuzzy measure for all the sensors meaning the subjective weights of the sensors on each object. Through recursive sensing process all the possible target objects have the cumulative decision measures (CDM), which are derived from fuzzy measures to represent possibilities that one object is the target to be identified. The properties and applicability of the proposed algorithm is analyzed.
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