{"title":"OWA背后的主要思想导致了一个通用的和最优的近似方案","authors":"Ronald R. Yager, V. Kreinovich","doi":"10.1109/NAFIPS.2002.1018098","DOIUrl":null,"url":null,"abstract":"In the arithmetic average, we combine all the estimates with equal weights. In some practical situations, it makes sense to give move weight to consistent estimates and less weight to estimates that axe far away from the consensus of the majority. Ordered weighted averaging (OWA) operators have been successfully applied in many practical problems. We explain this empirical success by showing that these operators are indeed guaranteed to work (i.e. universal), and that these operators are the best to use (in some reasonable sense).","PeriodicalId":348314,"journal":{"name":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","volume":"336 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Main ideas behind OWA lead to a universal and optimal approximation scheme\",\"authors\":\"Ronald R. Yager, V. Kreinovich\",\"doi\":\"10.1109/NAFIPS.2002.1018098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the arithmetic average, we combine all the estimates with equal weights. In some practical situations, it makes sense to give move weight to consistent estimates and less weight to estimates that axe far away from the consensus of the majority. Ordered weighted averaging (OWA) operators have been successfully applied in many practical problems. We explain this empirical success by showing that these operators are indeed guaranteed to work (i.e. universal), and that these operators are the best to use (in some reasonable sense).\",\"PeriodicalId\":348314,\"journal\":{\"name\":\"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)\",\"volume\":\"336 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2002.1018098\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2002.1018098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Main ideas behind OWA lead to a universal and optimal approximation scheme
In the arithmetic average, we combine all the estimates with equal weights. In some practical situations, it makes sense to give move weight to consistent estimates and less weight to estimates that axe far away from the consensus of the majority. Ordered weighted averaging (OWA) operators have been successfully applied in many practical problems. We explain this empirical success by showing that these operators are indeed guaranteed to work (i.e. universal), and that these operators are the best to use (in some reasonable sense).