Abstract
In regard to how to find the ideal result of reasoning mechanism, the standard of the largest entropy can offer its proper interpretation. Inspired by this observation, the intuitionistic entropy-induced symmetric implicational (IESI) algorithm is put forward in this study, and then extend it to the corresponding cooperative reasoning version. To begin with, the new IESI standards are given, which are improved versions of the previous symmetric implicational standard. Thenceforth, the inherent characteristics of result of the IESI algorithm are analyzed. In addition, unified results of such algorithm are given, and the fuzzy system via the IESI algorithm is constructed and analyzed. Lastly, its cooperative reasoning version is proposed for multiple inputs and multiple rules, while the corresponding optimal solutions are also gained.
This research is supported by the National Natural Science Foundation of China (Nos. 61673156, 61877016, 61672202, U1613217, 61976078).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Tang, Y.M., Pedrycz, W.: Oscillation-bound estimation of perturbations under Bandler-Kohout subproduct. IEEE Trans. Cybern. (2020). https://doi.org/10.1109/TCYB.2020.3025793
Wang, G.J.: On the logic foundation of fuzzy reasoning. Inf. Sci. 117(1), 47–88 (1999)
Guo, F.F., Chen, T.Y., Xia, Z.Q.: Triple I methods for fuzzy reasoning based on maximum fuzzy entropy principle. Fuzzy Syst. Math. 17(4), 55–59 (2003)
Luo, M.X., Liu, B.: Robustness of interval-valued fuzzy inference triple I algorithms based on normalized Minkowski distance. J. Logical Algebraic Methods Program. 86(1), 298–307 (2017)
Tang, Y.M., Liu, X.P.: Differently implicational universal triple I method of (1, 2, 2) type. Comput. Math. Appl. 59(6), 1965–1984 (2010)
Tang, Y.M., Ren, F.J.: Variable differently implicational algorithm of fuzzy inference. J. Intell. Fuzzy Syst. 28(4), 1885–1897 (2015)
Li, H.X.: Probability representations of fuzzy systems. Sci. China Ser. F-Inf. Sci. 49(3), 339–363 (2006)
Tang, Y.M., Yang, X.Z.: Symmetric implicational method of fuzzy reasoning. Int. J. Approximate Reason. 54(8), 1034–1048 (2013)
Tang, Y.M., Pedrycz, W.: On the \(\alpha \)(u, v)-symmetric implicational method for R- and (S, N)-implications. Int. J. Approximate Reason. 92, 212–231 (2018)
Tang, Y.M., Song, X.C., Ren, F.J., Pedrycz, W.: Entropy-based symmetric implicational method for R- and (S, N)-implications. In: IEEE ISKE 2019, pp. 683–688 (2019)
Szmidt, E., Kacprzyk, J.: Entropy for intuitionistic fuzzy sets. Fuzzy Sets Syst. 118(3), 467–477 (2001)
Zheng, M.C., Shi, Z.K., Liu, Y.: Triple I method of approximate reasoning on Atanassov’s intuitionistic fuzzy sets. Int. J. Approximate Reason. 55(6), 1369–1382 (2014)
Jayaram, B.: On the law of importation \((x\wedge y) \rightarrow z \equiv (x\rightarrow (y\rightarrow z))\) in fuzzy logic. IEEE Trans. Fuzzy Syst. 16(1), 130-144 (2008)
Tang, Y.M., Hu, X.H., Pedrycz, W., Song, X.C.: Possibilistic fuzzy clustering with high-density viewpoint. Neurocomputing 329(15), 407–423 (2019)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Tang, Y., Huang, J., Ren, F., Pedrycz, W., Bao, G. (2021). Intuitionistic Entropy-Induced Cooperative Symmetric Implicational Inference. In: Sun, Y., Liu, D., Liao, H., Fan, H., Gao, L. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2020. Communications in Computer and Information Science, vol 1330. Springer, Singapore. https://doi.org/10.1007/978-981-16-2540-4_11
Download citation
DOI: https://doi.org/10.1007/978-981-16-2540-4_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-2539-8
Online ISBN: 978-981-16-2540-4
eBook Packages: Computer ScienceComputer Science (R0)
