Skip to main content
SpringerLink
Log in
Book cover

International Conference on Theory and Applications of Fuzzy Systems and Soft Computing

ICAFS 2018: 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018 pp 568–576Cite as

Forecasting the Solvency of Legal Entities on the Base of Fuzzy Modeling of the Time Series of Their Financial Indicators

  • Conference paper
  • First Online:

  • 669 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 896))

Abstract

The methodology for assessing the prospective solvency of legal entities under uncertainty is considered on the base of fuzzy models predicting weakly structured time series of financial indicators and fuzzy method of multi-criteria choice of alternatives.

This is a preview of subscription content, 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   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
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

Learn about institutional subscriptions

References

  1. Andreichenkov, A.V., Andreichenkova, O.N.: Analysis, Synthesis, Planning Decisions in the Economy. Finance and Statistics, Moscow (2000). (in Russian)

    Google Scholar 

  2. Chen, S.M.: Forecasting enrollments based on fuzzy time series. Fuzzy Sets Syst. 81, 311–319 (1996)

    Article  Google Scholar 

  3. Chen, S.M.: Forecasting enrollments based on fuzzy time series. Cybern. Syst.: Int. J. 33, 1–16 (2002)

    Article  Google Scholar 

  4. Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Inf. Sci. 8(3), 199–249 (1965)

    Article  MathSciNet  Google Scholar 

  5. Rzayev, R.R.: Analytical Support for Decision-Making in Organizational Systems. Palmerium Academic Publishing, Saarbruchen (2016). (in Russian)

    Google Scholar 

Download references

Acknowledgement

The authors consider necessary to express their appreciation to Professor R.R. Rzayev for the help that he rendered during the process of writing and preparing this article.

Author information

Authors and Affiliations

  1. Institute of Control Systems of ANAS, Baku, AZ1141, Azerbaijan

    Elchin Aliyev, Hajar Shikhaliyeva & Zaur Gaziyev

  2. University College London, London, SE18YP, UK

    Adila Ali

Authors
  1. Elchin Aliyev
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hajar Shikhaliyeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zaur Gaziyev
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adila Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elchin Aliyev .

Editor information

Editors and Affiliations

  1. Joint MBA Program, Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Rafik A. Aliev

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  4. Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

    Mo. Jamshidi

  5. Department of Mechatronics, Near East University, Nicosia TRNC, Turkey

    Fahreddin M. Sadikoglu

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aliyev, E., Shikhaliyeva, H., Gaziyev, Z., Ali, A. (2019). Forecasting the Solvency of Legal Entities on the Base of Fuzzy Modeling of the Time Series of Their Financial Indicators. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_75

Download citation

Publish with us

Policies and ethics

Search

Navigation