{"title":"A semantics of the basic modal language based on a generalized rough set model","authors":"Md. Aquil Khan, Ranjan","doi":"10.1016/j.ins.2024.121838","DOIUrl":null,"url":null,"abstract":"<div><div>The necessity lower approximation operator defined on subset approximation structures is studied in this paper. We propose a semantics of the basic modal language based on this operator, offering a formal framework for analysis. The study focuses on the axiomatization, expressiveness, and invariance properties of the proposed semantics. Our findings contribute to a comprehensive understanding of the necessity lower approximation operator, shedding light on its properties.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"701 ","pages":"Article 121838"},"PeriodicalIF":8.1000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025524017523","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The necessity lower approximation operator defined on subset approximation structures is studied in this paper. We propose a semantics of the basic modal language based on this operator, offering a formal framework for analysis. The study focuses on the axiomatization, expressiveness, and invariance properties of the proposed semantics. Our findings contribute to a comprehensive understanding of the necessity lower approximation operator, shedding light on its properties.
期刊介绍:
Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions.
Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.