Skip to main content
SpringerLink
Log in

Generalized Net Model of Balanced Iterative Reducing and Clustering Using Hierarchies (Birch) with Intuitionistic Fuzzy Evaluations

  • Conference paper
  • First Online:
Intelligent and Fuzzy Systems (INFUS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 504))

Included in the following conference series:

  • 872 Accesses

Abstract

Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) is a method for agglomerative cluster analysis. A Generalized net (GN) model of the BIRCH is constructed. The clustering procedure is estimated using intuitionistic fuzzy evaluations. The process monitoring is explained using the constructed GN model and calculated IFEs. The GN model of BIRCH with IFEs optimizes and estimates the standard clustering algorithm. The proposed method is implemented using Python programming language.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Atanassov, K., Roeva, O., Pencheva, T., Shennon, A.: Generalized nets in artificial intelligence. In: Volume 7: Generalized Nets and Genetic Algorithms. Prof. Marin Drinov Academic Publishing House, Sofia (2013)

    Google Scholar 

  2. Atanassov, K., Sotirov, S.: Generalized nets as tools for modelling of the neural networks. In: 2020 IEEE 10th International Conference on Intelligent Systems, pp. 521–525 (2020)

    Google Scholar 

  3. Atanassov, K., Sotirov, S.: Generalized nets in artificial intelligence. In: Volume 6: Generalized Nets and Supervised Neural Network. Prof. Marin Drinov Academic Publishing House, Sofia (2012)

    Google Scholar 

  4. Atanassov, K., Sotirova, E.: Generalized Nets. Professor Marin Drinov Publishing House of Bulgarian Academy of Sciences, Sofia (2017). (in Bulgarian)

    Google Scholar 

  5. Atanassov, K.: Generalized Nets and Intuitionistic Fuzziness in Data Mining. Professor Marin Drinov Publishing House of Bulgarian Academy of Sciences, Sofia (2020)

    Google Scholar 

  6. Atanassov, K.: Generalized nets as a tool for the modelling of data mining processes. In: Sgurev, V., Yager, R.R., Kacprzyk, J., Jotsov, V. (eds.) Innovative Issues in Intelligent Systems. SCI, vol. 623, pp. 161–215. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-27267-2_6

    Chapter  Google Scholar 

  7. Atanassov, K.: Index Matrices: Towards an Augmented Matrix Calculus. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10945-9

  8. Atanassov, K.: Theory of generalized nets (an algebraic aspect). AMSE Rev. 1(2), 27–33 (1984)

    Google Scholar 

  9. Atanassov, K.: Generalized Nets. World Scientific, Singapore (1991)

    Book  Google Scholar 

  10. Atanassov, K.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20(1), 87–96 (1986)

    Article  Google Scholar 

  11. Atanassov, K.: Intuitionistic Fuzzy Sets: Theory and Applications. Physica-Verlag, Heidelberg (1999)

    Book  Google Scholar 

  12. Atanassov, K.: On Generalized Nets Theory. “Prof. M. Drinov” Academic Publ. House, Sofia (2007)

    Google Scholar 

  13. Atanassov, K.: On Intuitionistic Fuzzy Sets Theory. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-29127-2

    Book  MATH  Google Scholar 

  14. Bureva, V., Sotirova, E., Popov, S., Mavrov, D., Traneva, V.: Generalized net of cluster analysis process using STING: a statistical information grid approach to spatial data mining. In: Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T., Legind Larsen, H. (eds.) FQAS 2017. LNCS (LNAI), vol. 10333, pp. 239–248. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59692-1_21

    Chapter  Google Scholar 

  15. Bureva, V., Traneva, V., Zoteva, D., Tranev, S.: Generalized net model simulation of cluster analysis using CLIQUE: clustering in quest. In: Dimov, I., Fidanova, S. (eds.) HPC 2019. SCI, vol. 902, pp. 48–60. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-55347-0_5

    Chapter  Google Scholar 

  16. Hassanien, A.E., Azar, A.T., Snasael, V., Kacprzyk, J., Abawajy, J.H. (eds.): Big Data in Complex Systems. SBD, vol. 9. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-11056-1

    Book  Google Scholar 

  17. Ikonomov, N.: GNDraw – software application for creating generalized nets. Issues Intuitionistic Fuzzy Sets Generalized Nets 13, 61–71 (2017)

    Google Scholar 

  18. Zhang, T., Ramakrishnan, R., Livny, M.: BIRCH: an efficient data clustering method for very large databases. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data – SIGMOD’96, pp. 103–114 (1996)

    Google Scholar 

Download references

Acknowledgments

The authors are grateful for the support provided by the European Regional Development Fund and the Operational Program “Science and Education for Smart Growth” under contract UNITe No. BG05M2OP001-1.001-0004-C01 (2018–2023).

Author information

Authors and Affiliations

  1. Laboratory of Intelligent Systems, “Prof. Dr. AssenZlatarov” University, “Prof. Yakimov” Blvd., Burgas, 8010, Bulgaria

    Veselina Bureva, Petar Petrov & Stanislav Popov

  2. Vocational School of Electrical Engineering and Electronics, “Konstantin Fotinov”, Burgas, Bulgaria

    Petar Petrov

Authors
  1. Veselina Bureva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Petar Petrov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stanislav Popov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Veselina Bureva .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  3. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Department of Industrial Engineering, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  5. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Basar Oztaysi

  6. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bureva, V., Petrov, P., Popov, S. (2022). Generalized Net Model of Balanced Iterative Reducing and Clustering Using Hierarchies (Birch) with Intuitionistic Fuzzy Evaluations. In: Kahraman, C., Tolga, A.C., Cevik Onar, S., Cebi, S., Oztaysi, B., Sari, I.U. (eds) Intelligent and Fuzzy Systems. INFUS 2022. Lecture Notes in Networks and Systems, vol 504. Springer, Cham. https://doi.org/10.1007/978-3-031-09173-5_78

Download citation

Publish with us

Policies and ethics

Search

Navigation