Skip to main content
SpringerLink
Log in

An Algorithm for Setting Sugeno-Type Fuzzy Inference Systems

  • INTELLIGENT SYSTEMS
  • Published:
Automatic Documentation and Mathematical Linguistics Aims and scope

Abstract

An algorithm for tuning fuzzy inference systems of the Sugeno type of zero order based on statistical data is presented, which assumes the allocation of a set of reference points in the space of input variables, where the values of the output variable are calculated using linear regression. The results of the algorithm are presented, showing the effectiveness of its application for the synthesis of intelligent information systems for various purposes.

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.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.

Similar content being viewed by others

REFERENCES

  1. Pegat, A., Nechetkoe modelirovanie i upravlenie (Fuzzy Modeling and Control), Moscow: Binom, 2013.

  2. Tobin, D.S., A network expert-analytical platform as a tool to support decision-making in a distributed environment, Vestn. Novosib. Gos. Univ. Ekon. Upr., 2020, no. 3, pp. 231–240.

  3. Katasev, A.S., A neuro-fuzzy model for the formation of fuzzy rules for assessing the state of objects in conditions of uncertainty, Komp’yut. Issled. Model., 2019, vol. 11, no. 3, pp. 477–492.

    Google Scholar 

  4. Bogomolov, A.V., Synthesis of an expression for calculating the index of conformity of an object to alternative classes based on the results of multidimensional statistical classification, Inf. Tekhnol., 1999, no. 12, p. 45.

  5. Kosko, B., Fuzzy systems as universal approximators, IEEE Trans. Comput., 1994, vol. 43, no. 11, pp. 1329–1333.

    Article  Google Scholar 

  6. Kosko, B., Global stability of generalized additive fuzzy systems, IEEE Trans. Syst. Man Cybern., Part C: Appl. Rev., 1998, vol. 28, no. 3, pp. 441–452.

    Article  Google Scholar 

  7. Manentia, F., Rossia, F., Goryunov, A., Dyadik, A., Kozin, K., Nadezhdin, I., and Mikhalevich, S., Fuzzy adaptive control system of a non-stationary plant with closed-loop passive identifier, Resour.-Efficient Technol., 2015, vol. 1, no. 1, pp. 10–18.

    Article  Google Scholar 

  8. Golosovskiy, M.S., An algorithm for local tuning of systems of fuzzy logical inference of the Mamdani type with preservation of the interpretability of production rules, Upr. Bol’shimi Sist., 2018, no. 74, pp. 6–22.

  9. Golosovskiy, M.S., Bogomolov, A.V., Terebov, D.S., and Evtushenko, E.V., An algorithm for tuning a fuzzy logical inference system of the Mamdani type, Vestn. Yuzhno-Ural. Gos. Univ., Ser.: Mat. Mekh. Fiz., 2018, vol. 10, no. 3, pp. 19–29.

    Google Scholar 

  10. Dreiper, N. and Smit, G., Prikladnoi regressionnyi analiz (Applied Regression Analysis), Moscow: Dialektika, 2016.

  11. Larkin, E., Bogomolov, A., and Privalov, A., Data buffering in information-measuring system, 2nd International Ural Conference on Measurements (UralCon), Chelyabinsk: SUSU, 2017, pp. 118–123. https://doi.org/10.1109/URALCON.2017.8120697

  12. Bychkov, E.V., Bogomolov, A.V., and Kotlovanov, K.Yu., Stochastic mathematical model of internal waves, Bull. South Ural State Univ., Ser.: Math. Modell. Program. Comput. Software, 2020, vol. 13, no. 2, pp. 33–42. https://doi.org/10.14529/mmp200203

    Article  MATH  Google Scholar 

Download references

Funding

This study was supported by a grant from the President of the Russian Federation for state support of leading scientific schools of the Russian Federation (NSh-2553.2020.8).

Author information

Authors and Affiliations

  1. St. Petersburg Federal Research Center, Russian Academy of Sciences, 199178, St. Petersburg, Russia

    M. S. Golosovskiy, A. V. Bogomolov & E. V. Evtushenko

Authors
  1. M. S. Golosovskiy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. V. Bogomolov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. V. Evtushenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to M. S. Golosovskiy, A. V. Bogomolov or E. V. Evtushenko.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Golosovskiy, M.S., Bogomolov, A.V. & Evtushenko, E.V. An Algorithm for Setting Sugeno-Type Fuzzy Inference Systems. Autom. Doc. Math. Linguist. 55, 79–88 (2021). https://doi.org/10.3103/S000510552103002X

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S000510552103002X

Keywords:

Search

Navigation