{"title":"基于邻域系统的一些隶属函数在粗糙集决策中的应用","authors":"A. E. F. El Atik, A. Zedan","doi":"10.5269/bspm.51936","DOIUrl":null,"url":null,"abstract":"The neighborhood structure can represent information or knowledge about relationships between a universe's object. In other words, such elements or objects are somewhat similar to that element in an element's neighborhood. Pawlak presented the idea of rough sets as useful tools for learning computer science and information systems. Neighborhood structures used this principle to be generalized and studied. This paper uses a neighborhood method to solve several rough set theory problems. By using a neighborhood of objects in the information system and illustrative examples to apply it, we introduce some new definitions of attributes, membership function and accuracy measurement. A decision making of our method gives an accurate decision and helps with decision correlation to calculate the accuracy of each attribute that builds an approach to decision making.","PeriodicalId":44941,"journal":{"name":"Boletim Sociedade Paranaense de Matematica","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Some membership functions via neighborhood systems: application to a rough set decision making\",\"authors\":\"A. E. F. El Atik, A. Zedan\",\"doi\":\"10.5269/bspm.51936\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The neighborhood structure can represent information or knowledge about relationships between a universe's object. In other words, such elements or objects are somewhat similar to that element in an element's neighborhood. Pawlak presented the idea of rough sets as useful tools for learning computer science and information systems. Neighborhood structures used this principle to be generalized and studied. This paper uses a neighborhood method to solve several rough set theory problems. By using a neighborhood of objects in the information system and illustrative examples to apply it, we introduce some new definitions of attributes, membership function and accuracy measurement. A decision making of our method gives an accurate decision and helps with decision correlation to calculate the accuracy of each attribute that builds an approach to decision making.\",\"PeriodicalId\":44941,\"journal\":{\"name\":\"Boletim Sociedade Paranaense de Matematica\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Boletim Sociedade Paranaense de Matematica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5269/bspm.51936\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Boletim Sociedade Paranaense de Matematica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5269/bspm.51936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS","Score":null,"Total":0}
Some membership functions via neighborhood systems: application to a rough set decision making
The neighborhood structure can represent information or knowledge about relationships between a universe's object. In other words, such elements or objects are somewhat similar to that element in an element's neighborhood. Pawlak presented the idea of rough sets as useful tools for learning computer science and information systems. Neighborhood structures used this principle to be generalized and studied. This paper uses a neighborhood method to solve several rough set theory problems. By using a neighborhood of objects in the information system and illustrative examples to apply it, we introduce some new definitions of attributes, membership function and accuracy measurement. A decision making of our method gives an accurate decision and helps with decision correlation to calculate the accuracy of each attribute that builds an approach to decision making.