Have a personal or library account? Click to login
Method of Constructing the Fuzzy Regression Model of Bank Competitiveness Cover

Method of Constructing the Fuzzy Regression Model of Bank Competitiveness

Open Access
|May 2018

References

  1. 1. Aliev, P. (1991). Production management under fuzzy initial information [Upravleniye proizvodstvom pri nechetkoy iskhodnoy informatsii]. Moscow: Energoatomizdat.
  2. 2. Andasarova, R. (2016). Credit risk management in banks under the Basel accord and IFRS 9: challenges and projections. Economic Studies, 3, 45-59.
  3. 3. Diamond, P. (1988). Fuzzy least squares. Information Science, 46, 141–157.10.1016/0020-0255(88)90047-3
  4. 4. Celmins, A. (1987). Least squares model fitting to fuzzy vector data. Fuzzy Sets and Systems, 22, 260–269.10.1016/0165-0114(87)90070-4
  5. 5. Kao, C. (2005). Entropy for fuzzy regression analysis. International Journal of Systems Science, 36, 869 – 876.10.1080/00207720500382290
  6. 6. Krivonozhko, V. (2010). Analysis of complex socio-economic systems [Analiz slozhnykh sotsial’no-ekonomicheskikh sistem]. Moscow: MAKS Press.
  7. 7. Ponomarenko, V. & Malyarets, L. (2009). Multidimensional analysis of socio-economic systems [Bahatovymirnyy analiz sotsial’noekonomichnykh system]. Kharkiv: KhNUE.
  8. 8. Redden, D. (1994). Properties of certain fuzzy linear regression methods. Fuzzy Sets and Systems, 64, 361–375.10.1016/0165-0114(94)90159-7
  9. 9. Sakawa, M. (1992). Multiobjective fuzzy linear regression analysis for fuzzy input-output data. Fuzzy Sets and Systems, 47, 173–181.10.1016/0165-0114(92)90175-4
  10. 10. Sapkina, N. (2013). Fuzzy linear regression and correlation [Nechetkaya parnaya lineynaya regressiya i korrelyatsiya]. The modern economy: problems and solutions: scientific-practical Journal [Sovremennaya ekonomika: problemy i resheniya: nauch.-prakt. zhurnal], 10(46), 178–189.
  11. 11. Shtovba, S. (2006). Fuzzy identification based on regression models parametric membership functions [Nechetkaya identifikatsiya na osnove regressionnykh modeley parametricheskoy funktsii prinadlezhnosti]. Problems of Control and Informatics [Problemy upravleniya i informatiki], 6, 38–44.
  12. 12. Tanaka, H. (1982). Linear regression analysis with fuzzy model. IEEE Transactions on Systems, Man and Cybernetics, 12, 903 – 907.10.1109/TSMC.1982.4308925
  13. 13. Vojcheska, K. (2013). Opportunities for complex analysis of the bank system. Economic Studies, 4, 67-78.
  14. 14. Wang, H. (2000). Resolution of fuzzy regression model. European Journal of Operational research, 126, 637–650.10.1016/S0377-2217(99)00317-3
  15. 15. Yager, R. (1986). A characterization of the extension principle. Fuzzy Sets and Systems, 18, 205–217.10.1016/0165-0114(86)90002-3
  16. 16. Yang, M. (2002). Fuzzy least-squared linear regression analysis for fuzzy input-output data. Fuzzy Sets and Systems, 126(3), 389–399.10.1016/S0165-0114(01)00066-5
  17. 17. Yarushkina, N. (2010). Intellectual time series analysis [Intellektual’nyy analiz vremennykh ryadov]. Ulyanovsk: UlSTU.
  18. 18. Zade, L. (2001). From computing with numbers to computing with words – from manipulation of measurements to manipulation of perceptions. Computing With Words. New York: Wiley and Sons.10.1063/1.1388678
Language: English
Page range: 139 - 164
Submitted on: May 4, 2017
|
Accepted on: Aug 14, 2017
|
Published on: May 14, 2018
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2018 Liudmyla Malyaretz, Oleksandr Dorokhov, Liudmyla Dorokhova, published by Central Bank of Montenegro
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.