Skip to main content
SpringerLink
Log in

A further study on optimal scale selection in dynamic multi-scale decision information systems based on sequential three-way decisions

  • Original Article
  • Published:
International Journal of Machine Learning and Cybernetics Aims and scope Submit manuscript

Abstract

The optimal scale selection is the key problem in the study of multi-scale decision information systems. Dynamic change is one of the main features of big data, and the amount of information will often increase sharply with the passing of time. As is well known, the issue of updating the optimal scale of a multi-scale decision information system has been becoming a challenging problem in recent years, and it indeed has important theoretical and practical research values. Note that adding multiple objects can be viewed as adding one object multiple times. So, it just needs to clarify the change laws of optimal scale under the case of adding one object. Although the existing work has considered this problem in terms of the sufficient condition of updating the optimal scale, the results seem to be inaccurate. In other words, both sufficient and necessary conditions are still missing. In this paper, using sequential three-way decisions, the sufficient and necessary conditions of updating the optimal scale of a multi-scale decision information system are developed for the addition of an object, which makes the theoretical study on updating the optimal scale more complete.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Chen YS, Li JJ, Huang JX (2019) Matrix method for the optimal scale selection of multi-scale information decision systems. Mathematics 290:3–17

    Google Scholar 

  2. Chen YL, Zhang QH, Wang GY, Hu BQ (2020) Optimal scale selection and attribute reduction in multi-scale decision tables based on three-way decision. Inform Sci 541:36–59

    Article  MathSciNet  Google Scholar 

  3. Hao C, Li JH, Min F, Liu WQ, Tsang ECC (2017) Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions. Inform Sci 415:213–232

    Article  Google Scholar 

  4. Hu MJ, Yao YY (2019) Structured approximations as a basis for three-way decisions in rough set theory. Knowl Based Syst 165:92–109

    Article  Google Scholar 

  5. Huang ZH, Li JJ (2021) Discernibility measures for fuzzy covering and their application. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2021.3054742

  6. Huang ZH, Li JJ, Dai WZ, Lin RD (2019) Generalized multi-scale decision tables with multi-scale decision attributes. Int J Approx Reason 115:194–208

    Article  MathSciNet  Google Scholar 

  7. Huang QQ, Li TR, Huang YY (2020) Incremental three-way neighborhood approach for dynamic incomplete hybrid data. Inform Sci 541:98–122

    Article  MathSciNet  Google Scholar 

  8. Li F, Hu BQ (2017) A new approach of optimal scale selection to multi-scale decision tables. Inform Sci 381:193–208

    Article  Google Scholar 

  9. Li F, Hu BQ (2017) Stepwise optimal scale selection for multi-scale decision tables via attribute significance. Knowl Based Syst 129:4–16

    Article  Google Scholar 

  10. Li JH, Mei CL, Xu WH, Qian YH (2015) Concept learing via granular computing: a cognitive viewpoint. Inform Sci 298:447–467

    Article  MathSciNet  Google Scholar 

  11. Li JH, Huang CC, Qi JJ, Qian YH, Liu WQ (2017) Three way cognitive concept learing via multi-granularity. Inform Sci 378:244–263

    Article  Google Scholar 

  12. Li WK, Li JJ, Huang JX, Dai WZ, Zhang XP (2021) A new rough set model based on multi-scale covering. Int J Mach Learn Cybern 12(1):243–256

    Article  Google Scholar 

  13. Lin TY (1997) Granular computing: From rough sets and neighborhood systems to information granulation and computing with words. European Congress on Intelligent Techniques and Soft Computing. Aachen, Germany, pp 1602–1606

  14. Luo C, Li TR, Chen H et al (2018) Incremental rough set approach for hierarchical multicriteria classification. Inform Sci 429:72–87

    Article  MathSciNet  Google Scholar 

  15. Luo C, Li TR, Huang YY, Fujita H (2019) Updating three-way decisions in incomplete multi-scale information systems. Inform Sci 476:274–289

    Article  Google Scholar 

  16. Pedrycz W (2001) Granular computing: an emerging paradigm. Physica, Heidelberg

    Book  Google Scholar 

  17. Qian YH, Liang JY, Yao YY, Dang CY (2010) MGRS: a multi-granulation rough set. Inform Sci 180(6):949–970

    Article  MathSciNet  Google Scholar 

  18. She YH, Qian YH, He XL, Wang JT, Qian T, Zheng WL (2021) On generalization reducts in multi-scale decision tables. Inform Sci 555:104–124

    Article  MathSciNet  Google Scholar 

  19. Tan AH, Shi SW, Wu WZ, Li JJ, Pedrycz W (2020) Granularity and entropy of intuitionistic fuzzy information and their applications. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.2973379

  20. Wu WZ, Leung Y (2011) Theory and applications of granular labelled partitions in multi-scale decision tables. Inform Sci 181(18):3878–3897

    Article  Google Scholar 

  21. Wu WZ, Qian YH, Li TJ, Gu SM (2017) On rule acquisition in incomplete multi-scale decision tables. Inform Sci 378:282–302

    Article  MathSciNet  Google Scholar 

  22. Xie JP, Yang MH, Li JH, Zheng Z (2018) Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart city. Fut Gen Comput Syst 83:564–581

    Article  Google Scholar 

  23. Xu WH, Li WT (2016) Granular computing approach to two-way learning based on formal concept analysis in fuzzy datasets. IEEE Trans Cybern 46(2):366–379

    Article  MathSciNet  Google Scholar 

  24. Xu WH, Yu JH (2017) A novel approach to information fusion in multi-source datasets: a granular computing viewpoint. Inform Sci 378:410–423

    Article  Google Scholar 

  25. Yang XB, Zhang YQ, Yang JY (2012) Local and global measurements of MGRS rules. Int J Comput Intell Syst 5(6):1010–1024

    Article  MathSciNet  Google Scholar 

  26. Yang L, Xu WH, Zhang XY, Sang BB (2020) Multi-granulation method for information fusion in multi-source decision information system. Int J Approx Reason 122:47–65

    Article  MathSciNet  Google Scholar 

  27. Yao YY, Deng XF (2011) Sequential three-way decisions with probabilistic rough sets. In: Proceedings of the 10th IEEE international conference on cognitive informatics and cognitive computing, Banff, Canada, pp 120–125

  28. Yao YY (2001) Information granulation and rough set approximation. Int J Intell Syst 16:87–104

    Article  MathSciNet  Google Scholar 

  29. Zadeh LA (1997) Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 90:111–127

    Article  MathSciNet  Google Scholar 

  30. Zhang XQ, Zhang QH, Chen YL, Wang GY (2020) Optimal scale selection by integrating uncertainty and cost sensitive learning in multi-scale decision tables. Int J Mach Learn Cybern 11(5):1095–1114

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 11701258, 11871259, 11971211).

Author information

Authors and Affiliations

  1. School of Mathematics Sciences, Huaqiao University, Quanzhou, 362021, Fujian, People’s Republic of China

    Yingsheng Chen, Jinjin Li, Rongde Lin & Dongxiao Chen

  2. Fujian Province University Key Laboratory of Computational Science, Huaqiao University, Quanzhou, 362021, Fujian, People’s Republic of China

    Yingsheng Chen, Jinjin Li, Rongde Lin & Dongxiao Chen

  3. Data Science Research Center, Kunming University of Science and Technology, Kunming, 650500, Yunnan, People’s Republic of China

    Jinhai Li

Authors
  1. Yingsheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jinhai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jinjin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rongde Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dongxiao Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jinhai Li.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Li, J., Li, J. et al. A further study on optimal scale selection in dynamic multi-scale decision information systems based on sequential three-way decisions. Int. J. Mach. Learn. & Cyber. 13, 1505–1515 (2022). https://doi.org/10.1007/s13042-021-01474-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13042-021-01474-7

Keywords

Search

Navigation