Vector-based approaches for computing approximations in multigranulation rough set
Approximation computation is a significant issue when the rough set model is applied. However, few authors focus on how to calculate approximations of multigranulation rough set (MGRS). Herein, the authors clarify a fact that only a part of elements in the universe need to be judged whether they bel...
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| Vydáno v: | Journal of engineering (Stevenage, England) Ročník 2018; číslo 16; s. 1538 - 1543 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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The Institution of Engineering and Technology
01.11.2018
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| ISSN: | 2051-3305, 2051-3305 |
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| Abstract | Approximation computation is a significant issue when the rough set model is applied. However, few authors focus on how to calculate approximations of multigranulation rough set (MGRS). Herein, the authors clarify a fact that only a part of elements in the universe need to be judged whether they belong to approximations of MGRS. If X is a target concept which is approximated by approximations in MGRS, then the element whose equivalence class does not intersect with X is of no need to be judged. Based on the fact, the authors clarify that they proposed a vector-based algorithm to compute approximations in MGRS. Time complexity of the proposed algorithm is $O\lpar {\vert X\vert} {\vert U\vert} \rpar $O(|X||U|). |
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| AbstractList | Approximation computation is a significant issue when the rough set model is applied. However, few authors focus on how to calculate approximations of multigranulation rough set (MGRS). Herein, the authors clarify a fact that only a part of elements in the universe need to be judged whether they belong to approximations of MGRS. If X is a target concept which is approximated by approximations in MGRS, then the element whose equivalence class does not intersect with X is of no need to be judged. Based on the fact, the authors clarify that they proposed a vector‐based algorithm to compute approximations in MGRS. Time complexity of the proposed algorithm is . Approximation computation is a significant issue when the rough set model is applied. However, few authors focus on how to calculate approximations of multigranulation rough set (MGRS). Herein, the authors clarify a fact that only a part of elements in the universe need to be judged whether they belong to approximations of MGRS. If X is a target concept which is approximated by approximations in MGRS, then the element whose equivalence class does not intersect with X is of no need to be judged. Based on the fact, the authors clarify that they proposed a vector‐based algorithm to compute approximations in MGRS. Time complexity of the proposed algorithm is O ( | X | | U | ). Approximation computation is a significant issue when the rough set model is applied. However, few authors focus on how to calculate approximations of multigranulation rough set (MGRS). Herein, the authors clarify a fact that only a part of elements in the universe need to be judged whether they belong to approximations of MGRS. If X is a target concept which is approximated by approximations in MGRS, then the element whose equivalence class does not intersect with X is of no need to be judged. Based on the fact, the authors clarify that they proposed a vector-based algorithm to compute approximations in MGRS. Time complexity of the proposed algorithm is $O\lpar {\vert X\vert} {\vert U\vert} \rpar $O(|X||U|). |
| Author | Li, Jinjin Lin, Guoping Yu, Peiqiu |
| Author_xml | – sequence: 1 givenname: Peiqiu surname: Yu fullname: Yu, Peiqiu organization: 2Lab of Granular Computing, Fujian, Zhangzhou 363000, People's Republic of China – sequence: 2 givenname: Jinjin surname: Li fullname: Li, Jinjin email: jinjinli@mnnu.edu.cn organization: 2Lab of Granular Computing, Fujian, Zhangzhou 363000, People's Republic of China – sequence: 3 givenname: Guoping surname: Lin fullname: Lin, Guoping organization: 2Lab of Granular Computing, Fujian, Zhangzhou 363000, People's Republic of China |
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| Cites_doi | 10.1016/j.knosys.2012.12.003 10.1016/j.ijar.2013.03.004 10.1016/j.ijar.2013.05.004 10.1016/j.fss.2011.01.016 10.1016/S0167-8655(02)00196-4 10.1016/j.artint.2010.04.018 10.1016/j.ijar.2013.11.001 10.1016/j.ijar.2013.10.003 10.1016/j.ijar.2007.05.001 10.1007/978-3-540-27794-1_4 10.1016/j.ins.2009.11.023 10.1016/j.knosys.2017.01.030 10.1016/j.ijar.2007.05.019 10.1016/j.ins.2009.09.021 10.1016/j.ins.2006.06.006 10.1016/j.neucom.2013.11.027 10.1016/j.ijar.2013.02.013 10.1016/j.ins.2012.02.065 10.1007/BF01001956 |
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| Keywords | approximation theory multigranulation rough set vectors vector-based algorithm time complexity vector-based approaches rough set theory approximation computation rough set model computational complexity MGRS |
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| SubjectTerms | approximation computation approximation theory computational complexity MGRS multigranulation rough set rough set model rough set theory The 2nd 2018 Asian Conference on Artificial Intelligence Technology (ACAIT 2018) time complexity vectors vector‐based algorithm vector‐based approaches |
| Title | Vector-based approaches for computing approximations in multigranulation rough set |
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