Incrementally updating approximations based on the graded tolerance relation in incomplete information tables-Reference-Cited by-同舟云学术

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Incrementally updating approximations based on the graded tolerance relation in incomplete information tables

Published:2020-04-06 Issue:12 Volume:24 Page:8655-8671
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Luo Junfang,Qin Keyun,Zhang Yimeng,Zhao Xue Rong

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-020-04838-3.pdf

Reference52 articles.

1. Baczyński M, Jayaram B (2008) An introduction to fuzzy implications. In: Baczynski M, Jayaram B (eds) Fuzzy implications. Springer, Berlin, pp 1–35. https://doi.org/10.1007/978-3-540-69082-5_1

2. Chan CC (1998) A rough set approach to attribute generalization in data mining. Inf Sci 107(1–4):169–176. https://doi.org/10.1016/s0020-0255(97)10047-0

3. Chen HM, Li TR, Qiao SJ, Ruan D (2010) A rough set based dynamic maintenance approach for approximations in coarsening and refining attribute values. Int J Intell Syst 25(10):1005–1026. https://doi.org/10.1002/int.20436

4. Chen HM, Li TR, Ruan D, Lin JH, Hu CX (2013) A rough-set-based incremental approach for updating approximations under dynamic maintenance environments. IEEE Trans Knowl Data Eng 25(2):274–284. https://doi.org/10.1109/tkde.2011.220

5. Chen HM, Li TR, Luo C, Horng SJ, Wang GY (2014) A rough set-based method for updating decision rules on attribute values’ coarsening and refining. IEEE Trans Knowl Data Eng 26(12):2886–2899. https://doi.org/10.1109/tkde.2014.2320740

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Possible Equivalent Value Set for Incomplete Data Set;Computational Science and Its Applications – ICCSA 2023 Workshops;2023

2. Object-First Incremental Algorithms for Updating Approximations in Multi-Granulation Fuzzy Probabilistic Rough Sets Over Two Universes;IEEE Access;2021

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