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Since neighborhood multigranulation rough sets(NMGRS) were proposed, few papers focused on how to calculate approximations in NMGRS and how to update them dynamically. Here we propose approaches for computing approximations in NMGRS and updating them dynamically. First, static approaches for computing approximations in NMGRS are proposed. Second, search region in data set for updating approximations in NMGRS is shrunk. Third, matrix-based approaches for updating approximations in NMGRS while decreasing or increasing neighborhood classes are proposed. Fourth, incremental algorithms for updating approximations in NMGRS while decreasing or increasing neighborhood classes are designed. Finally, the efficiency and validity of the designed algorithms are verified by experiments.<\/jats:p>","DOI":"10.3233\/jifs-190034","type":"journal-article","created":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T12:44:47Z","timestamp":1561466687000},"page":"2847-2867","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Matrix-based approaches for updating approximations in neighborhood multigranulation rough sets while neighborhood classes decreasing or increasing"],"prefix":"10.1177","volume":"37","author":[{"given":"Peiqiu","family":"Yu","sequence":"first","affiliation":[{"name":"School of Mathematics and Statistics, Minnan normal university, Fujian, Zhangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongkun","family":"Wang","sequence":"additional","affiliation":[{"name":"Georgetown University, Georgetown, Washington DC, 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