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Interval type-2 fuzzy systems on the basis of vague partitions and their approximation properties

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Abstract

This article mainly focuses on simplifying the structure of interval type-2 (IT2) fuzzy system and studying its approximation properties. First of all, we construct the interval type-2 vague partitions (IT2-VPs) on input universe by overlap functions and vague partition of each attribute, and their properties are characterized. On the basis of these, we give the model of IT2 fuzzy system based on IT2-VPs, which mainly consists of the fuzzy rule base and center-of-sets type-reduction (TR). Next, we investigate its universal approximation property and approximation accuracy by error remainder term and auxiliary function method in numerical analysis. Finally, two comparative experiments indicate that the approximation performance of the proposed IT2 fuzzy systems can achieve better than the typical type-1 (T1) and IT2 fuzzy systems.

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References

  • Bustince H, Fernandez J, Mesiar R et al (2010) Overlap functions. Nonlinear Anal. 72(3–4):1488–1499

    MathSciNet  Google Scholar 

  • Chen Y (2020) Study on sampling-based discrete noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems. Soft Comput. 24:11819–11828

    Google Scholar 

  • Chen Y, Yang JX (2021) Study on center-of-sets type-reduction of interval type-2 fuzzy logic systems with noniterative algorithms. J. Intell. Fuzzy Syst. 40(6):11099–11106

    Google Scholar 

  • Chen Y, Wu JX, Lan J (2020a) Study on reasonable initialization enhanced Karnik-Mendel algorithms for centroid type-reduction of interval type-2 fuzzy logic systems. AIMS Math. 5(6):6149–6168

    MathSciNet  Google Scholar 

  • Chen Y, Wu JX, Lan J (2020b) Study on weighted-based noniterative algorithms for centroid type-reduction of interval type-2 fuzzy logic systems. AIMS Math. 5(6):7719–7745

    Google Scholar 

  • D’Alterio P, Garibaldi JM, John RI et al (2021) A fast inference and type-reduction process for constrained interval type-2 fuzzy systems. IEEE Trans. Fuzzy Syst. 29–11:3323–3333

    Google Scholar 

  • De Hierro AFRL, Roldán C, Tíscar MÁ et al (2022) Type-\((2, k) \) overlap indices. IEEE Trans. Fuzzy Syst. 31(3):860–874

    Google Scholar 

  • De Miguel L, Gómez D, Rodríguez JT et al (2019) General overlap functions. Fuzzy Sets Syst. 372:81–96

    MathSciNet  Google Scholar 

  • Dimuro GP, Bedregal B (2014) Archimedean overlap functions: the ordinal sum and the cancellation, idempotency and limiting properties. Fuzzy Sets Syst. 252:39–54

    MathSciNet  Google Scholar 

  • Dimuro GP, Bedregal B (2015) On residual implications derived from overlap functions. Inf. Sci. 312:78–88

    MathSciNet  Google Scholar 

  • Dimuro GP, Bedregal B (2017) QL-operations and QL-implication functions constructed from tuples (O, G, N) and the generation of fuzzy subsethood and entropy measures. Int. J. Approx. Reason. 82:170–192

    MathSciNet  Google Scholar 

  • Elkano M, Galar M, Sanz JA et al (2018) Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems. Appl. Soft Comput. 67:728–740

    Google Scholar 

  • El-Nagar AM, El-Bardini M (2014) Simplified interval type-2 fuzzy logic system based on new type-reduction. J. Intell. Fuzzy Syst. 27(4):1999–2010

    MathSciNet  Google Scholar 

  • Gómez D, Rodríguez JT, Montero J et al (2016) n-dimensional overlap functions. Fuzzy Sets Syst. 287:57–75

    MathSciNet  Google Scholar 

  • Jiang MZ, Yuan XH (2018) A new type of fuzzy systems using pyramid membership functions (pmfs) and approximation properties. Soft Comput. 22(21):7103–7118

    Google Scholar 

  • Jiang G, Yuan HJ, Li PC et al (2018) A new approach to fuzzy dynamic fault tree analysis using the weakest n-dimensional t-norm arithmetic. Chin. J. Aeronaut. 31(7):1506–1514

    Google Scholar 

  • Karnik NN, Mendel JM (2001) Centroid of a type-2 fuzzy set. Inf. Sci. 132(1–4):195–220

    MathSciNet  Google Scholar 

  • Karnik NN, Mendel JM, Liang Q (1999) Type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 7(6):643–658

    Google Scholar 

  • Khooban MH, Gheisarnejad M (2020) A novel deep reinforcement learning controller based type-ii fuzzy system: frequency regulation in microgrids. IEEE Trans. Emerg. Top. Comput. Intell. 5(4):689–699

    Google Scholar 

  • Klement EP, Mesiar R, Pap E (2000) Triangular Norms. Springer, Berlin

    Google Scholar 

  • Kumbasar T (2016) Robust stability analysis and systematic design of single input interval type-2 fuzzy logic controllers. IEEE Trans. Fuzzy Syst. 24(3):675–694

    Google Scholar 

  • Li CD, Yi JQ, Zhang GQ (2013) On the monotonicity of interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 22(5):1197–1212

    Google Scholar 

  • Liang QL, Mendel JM (2000) Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Syst. 8(5):535–550

    Google Scholar 

  • Liu XW, Mendel JM, Wu DR (2012) Study on enhanced Karnik-Mendel algorithms: initialization explanations and computation improvements. Inf. Sci. 184(1):75–91

    MathSciNet  Google Scholar 

  • Lucca G, Sanz JA, Dimuro GP et al (2018) \(C_F\)-integrals: a new family of pre-aggregation functions with application to fuzzy rule-based classification systems. Inf. Sci. 435:94–110

    Google Scholar 

  • Pan XD, Xu Y (2017) Redefinition of the concept of fuzzy set based on vague partition from the perspective of axiomatization. Soft Comput. 22(6):1777–1789

    Google Scholar 

  • Qi GA, Li JR, Kang BY et al (2023) The aggregation of z-numbers based on overlap functions and grouping functions and its application on group decision-making. Inf. Sci. 623:857–899

    Google Scholar 

  • Qiao JS, Hu BQ (2017) On interval additive generators of interval overlap functions and interval grouping functions. Fuzzy Sets Syst. 332:19–55

    MathSciNet  Google Scholar 

  • Qiao JS, Hu BQ (2018a) On generalized migrativity property for overlap functions. Fuzzy Sets Syst. 357:91–116

    MathSciNet  Google Scholar 

  • Qiao JS, Hu BQ (2018b) On multiplicative generators of overlap and grouping functions. Fuzzy Sets Syst. 332:1–24

    MathSciNet  Google Scholar 

  • Singh DJ, Verma NK, Ghosh AK et al (2022) An application of interval type-2 fuzzy model based control system for generic aircraft. Appl. Soft Comput. 121(108):721

    Google Scholar 

  • Starczewski JT, Przybyszewski K, Byrski A et al (2022) A novel approach to type-reduction and design of interval type-2 fuzzy logic systems. J. Artif. Intell. Soft Comput. Res. 12(3):197–206

    Google Scholar 

  • Takahashi A, Takahashi S (2021) A new interval type-2 fuzzy logic system under dynamic environment: application to financial investment. Eng. Appl. Artif. Intell. 100(104):154

    Google Scholar 

  • Wang LX (1997) A Course in Fuzzy Systems & Control. Prentice-Hall, Upper Saddle River

    Google Scholar 

  • Wang HW (2020) Constructions of overlap functions on bounded lattices. Int. J. Approx. Reason. 125:203–217

    MathSciNet  Google Scholar 

  • Wang YT, Hu BQ (2022) Constructing overlap and grouping functions on complete lattices by means of complete homomorphisms. Fuzzy Sets Syst. 427:71–95

    MathSciNet  Google Scholar 

  • Wang TC, Tong SC, Yi JQ et al (2015) Adaptive inverse control of cable-driven parallel system based on type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 23(5):1803–1816

    Google Scholar 

  • Wang LK, Karimi HR, Gu JH (2021) Stability analysis for interval type-2 fuzzy systems by applying homogenous polynomially membership functions dependent matrices and switching technique. IEEE Trans. Fuzzy Syst. 29(2):203–212

    Google Scholar 

  • Wen XF, Zhang XH (2021) Overlap functions based (multi-granulation) fuzzy rough sets and their applications in MCDM. Symmetry 13(10):1–27

    Google Scholar 

  • Wu DR, Mendel JM (2009) Enhanced Karnik-Mendel algorithms. IEEE Trans. Fuzzy Syst. 17(4):923–934

    Google Scholar 

  • Wu DR, Mendel JM (2011) On the continuity of type-1 and interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 19(1):179–192

    Google Scholar 

  • Xiao B, Lam HK, Li HY (2017) Stabilization of interval type-2 polynomial-fuzzy-model-based control systems. IEEE Trans. Fuzzy Syst. 25(1):205–217

    Google Scholar 

  • Yang LH, Liu J, Wang YM et al (2021) Enhancing extended belief rule-based systems for classification problems using decomposition strategy and overlap function. Int. J. Mach. Learn. Cybern. 13(3):811–837

    Google Scholar 

  • Zhang XH, Lang R, Bustince H et al (2022) Pseudo overlap functions, fuzzy implications and pseudo grouping functions with applications. Axioms 11(11):593

    Google Scholar 

  • Zhu FQ, Wang XP (2023) Note on the homogeneity of overlap functions. Fuzzy Sets Syst. 454:199–207

    MathSciNet  Google Scholar 

  • Zorich VA (2016) Mathematical Analysis II. Springer, Berlin

    Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61673320).

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Correspondence to Xiaoyu Peng.

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Communicated by Graçaliz Pereira.

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Peng, X., Pan, X. Interval type-2 fuzzy systems on the basis of vague partitions and their approximation properties. Comp. Appl. Math. 43, 119 (2024). https://doi.org/10.1007/s40314-024-02629-2

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