On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory
Knowledge reduction of information systems is one of the most important parts of rough set theory in real-world applications. Based on the connections between the rough set theory and the theory of topology, a kind of topological reduction of incomplete information systems is discussed. In this stud...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2023-01-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2022-0214 |
| _version_ | 1811171939676323840 |
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| author | Li Changqing Zhang Yanlan |
| author_facet | Li Changqing Zhang Yanlan |
| author_sort | Li Changqing |
| collection | DOAJ |
| description | Knowledge reduction of information systems is one of the most important parts of rough set theory in real-world applications. Based on the connections between the rough set theory and the theory of topology, a kind of topological reduction of incomplete information systems is discussed. In this study, the topological reduction of incomplete information systems is characterized by belief and plausibility functions from evidence theory. First, we present that a topological space induced by a pair of approximation operators in an incomplete information system is pseudo-discrete, which deduces a partition. Then, the topological reduction is characterized by the belief and plausibility function values of the sets in the partition. A topological reduction algorithm for computing the topological reducts in incomplete information systems is also proposed based on evidence theory, and its efficiency is examined by an example. Moreover, relationships among the concepts of topological reduct, classical reduct, belief reduct, and plausibility reduct of an incomplete information system are presented. |
| first_indexed | 2024-04-10T17:22:50Z |
| format | Article |
| id | doaj.art-857fb0d6188b4192b759e310a02ed38e |
| institution | Directory Open Access Journal |
| issn | 2191-026X |
| language | English |
| last_indexed | 2024-04-10T17:22:50Z |
| publishDate | 2023-01-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Intelligent Systems |
| spelling | doaj.art-857fb0d6188b4192b759e310a02ed38e2023-02-05T08:27:16ZengDe GruyterJournal of Intelligent Systems2191-026X2023-01-013213415610.1515/jisys-2022-0214On numerical characterizations of the topological reduction of incomplete information systems based on evidence theoryLi Changqing0Zhang Yanlan1School of Mathematics and Statistics, Minnan Normal University, Zhang’zhou, Fu’jian 363000, ChinaCollege of Computer, Minnan Normal University, Zhang’zhou, Fu’jian 363000, ChinaKnowledge reduction of information systems is one of the most important parts of rough set theory in real-world applications. Based on the connections between the rough set theory and the theory of topology, a kind of topological reduction of incomplete information systems is discussed. In this study, the topological reduction of incomplete information systems is characterized by belief and plausibility functions from evidence theory. First, we present that a topological space induced by a pair of approximation operators in an incomplete information system is pseudo-discrete, which deduces a partition. Then, the topological reduction is characterized by the belief and plausibility function values of the sets in the partition. A topological reduction algorithm for computing the topological reducts in incomplete information systems is also proposed based on evidence theory, and its efficiency is examined by an example. Moreover, relationships among the concepts of topological reduct, classical reduct, belief reduct, and plausibility reduct of an incomplete information system are presented.https://doi.org/10.1515/jisys-2022-0214belief and plausibility functionsrough setevidence theoryincomplete information systemtopology |
| spellingShingle | Li Changqing Zhang Yanlan On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory Journal of Intelligent Systems belief and plausibility functions rough set evidence theory incomplete information system topology |
| title | On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| title_full | On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| title_fullStr | On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| title_full_unstemmed | On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| title_short | On numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| title_sort | on numerical characterizations of the topological reduction of incomplete information systems based on evidence theory |
| topic | belief and plausibility functions rough set evidence theory incomplete information system topology |
| url | https://doi.org/10.1515/jisys-2022-0214 |
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