Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Applying the fuzzy set theory and fuzzy logic, we construct a mathematical model for predicting the value of unrealized goods rests and demonstrate this model on an empirical example showing good correlation with the real data.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
65--69
Opis fizyczny
Bibliogr. 20 poz., rys., tab., wz.
Twórcy
autor
- Department of Higher Mathematics, Lviv Polytechnic National University. 79013 Lviv, Stepana Bandery str., 12
autor
- Department of Higher Mathematics, Lviv Polytechnic National University. 79013 Lviv, Stepana Bandery str., 12
Bibliografia
- 1. Liu Baoding, and Yian-Kui Liu. 2002. Expected value of fuzzy variable and fuzzy expected value models. IEEE Transactions on fuzzy systems Vol. 10, Nos. 4, 445-450.
- 2. J. van den Berg, U. Kaymak, and W.M. van den Bergh. 2004. Financial markets analysis by using a probabilistic fuzzy modelling approach. International Journal of Approximate Reasoning.Vol. 35-3, 291–305
- 3. Bojadziev G. and Bojadziev M. 1995. Fuzzy sets and fuzzy logic, applications. Vorld scientific. Mathematics.
- 4. Juravljova I. 2008. Application of fuzzy sets theory to the problems of an intellectual consumer’s capital management. Scientific papers Donetsk NTU. Vol. 33-2, 126-131. (in Ukrainian)
- 5. Gil-Lafuente A.M. 2005. Fuzzy Logic in Financial Analysis. Studies in Fuzziness and Soft Computing, Vol. 175
- 6. Korshevnjuk L. and Bydjuk P. 2003. Solution of the problem of distribution of investments on the basis of fuzzy logic conclusion. System researches and information technologies. Vol. 2, 34-42 (in Ukrainian)
- 7. Marushchak S. 2011. Methodology of estimation of enterprise’s economic security based on the fuzzy sets theory. Announcer Hmelnytsky NU. Vol 1, Nos. 5, 16-21. (in Ukrainian)
- 8. Matvijchuk A. 2010. Financial firmness modeling of enterprises with application of fuzzy logic theory, neural networks and discriminant analysis. Announcer NAS , Vol. 9. (in Ukrainian)
- 9. Novak V., Perfiljeva I., and Mochkorj I. 2006. Mathematical principles of the fuzzy logic. Fizmatlit. (in Russia)
- 10. Rotshtein O.P. and Jupanova M.O., and Sheverda V.M. 1994. Differential diagnostics of ischemic heart trouble on the basis of fuzzy logic. Announcer VPI Vol.3. Nos.32. (in Ukrainian)
- 11. Siavavko M. and Rybytska O. 2000. A mathematical modeling in the terms of uncertainty . Ukranian technologies. (in Ukrainian)
- 12. Siavavko M. 2007. Information system “Fuzzy expert”. Lviv National University. (in Ukrainian)
- 13. Siavavko M. 2011. Mathematic of hidden features. National university “Ostrog Akademy”. (in Ukrainian)
- 14. Shang K., and Hossen Z. 2013. Applying Fuzzy Logic to Risk Assessment and Decision-Making. Canadian institute of actuaries
- 15. Telenik S. and Bidjuk P., and Korshevnjuk L., and Hmeljuk V. 2008. The fuzzy logic based approach for problem of multicriterion expert estimation Problems of programming. Vol. 4, 73-83. (in Ukrainian)
- 16. Zadeh L.A. 1976. The Concept of a Linguistic Variable and its Application to Approximate Reasoning. Information Sciences.Vol.9:3. 43-80.
- 17. Zadeh L.A. 1983. The Role of Fuzzy Logic in the Management of Uncertainty in Expert Systems. Fuzzy Sets and Systems. Vol.11. 199-227.
- 18. Zadeh L.A. 1996. Fuzzy Logic = Computing With Words. IEEE Transactions on Fuzzy Systems. Vol. 4. 103-111.
- 19. Zapounidis C., Pardalos P.M., and Baourakis G.. 2001. Fuzzy Sets in Management, Economics and Marketing, World Scientific.
- 20. Zimmermann H. 1991. Fuzzy Set Theory and it’s Applications. Kluner Academic Publishers.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e950d45f-f14d-40d3-82e7-bab9a2a185cd