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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Veröffentlicht in:Journal of engineering (Stevenage, England) Jg. 2018; H. 16; S. 1538 - 1543
Hauptverfasser: Yu, Peiqiu, Li, Jinjin, Lin, Guoping
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 01.11.2018
Schlagworte:
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
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
ISSN:2051-3305, 2051-3305
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Zusammenfassung: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|).
ISSN:2051-3305
2051-3305
DOI:10.1049/joe.2018.8317