As of August 2024, International Journal "Notes on Intuitionistic Fuzzy Sets" is being indexed in Scopus.
Please check our Instructions to Authors and send your manuscripts to nifs.journal@gmail.com. Next issue: September/October 2024.

Open Call for Papers: International Workshop on Intuitionistic Fuzzy Sets • 13 December 2024 • Banska Bystrica, Slovakia/ online (hybrid mode).
Deadline for submissions: 16 November 2024.

Issue:Intuitionistic fuzzy estimation of the doctoral comprehensive examination

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
Revision as of 19:20, 8 May 2014 by Velin S. Andonov (talk | contribs) (New page: {{PAGENAME}} {{PAGENAME}} {{PAGENAME}} {{issue/title...)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search
shortcut
http://ifigenia.org/wiki/issue:nifs/20/2/119-125
Title of paper: Intuitionistic fuzzy estimation of the doctoral comprehensive examination
Author(s):
Evdokia Sotirova
Prof. Asen Zlatarov University, Burgas-8000, Bulgaria
esotirova@btu.bg
Anthony Shannon
Faculty of Engineering & IT, University of Technology, Sydney, NSW 2007, Australia
Anthony.Shannon@uts.edu.au
Sotir Sotirov
Prof. Asen Zlatarov University, Burgas-8000, Bulgaria
ssotirov@btu.bg


Maciej Krawczak
Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Systems Research Institute – Polish Academy of Sciences, Wyzsza Szkola Informatyki Stosowanej i Zarzadzania, Warsaw, Poland
krawczak@ibspan.waw.pl
Published in: "Notes on IFS", Volume 20, 2014, Number 2, pages 119-125
Download:  PDF (332  Kb, File info)
Abstract: This paper describes a method for determining an intuitionistic fuzzy estimation of PhD candidature using the theories of Index Matrices and Intuitionistic Fuzzy Sets. The estimated degrees of satisfaction of the criteria by candidates are clustered by a neural network. In this way the procedure for assessment of the candidates for the dissertation stage can be measured and analyzed.
Keywords: Intuitionistic Fuzzy Sets, Index Matrices, Self-organizing Maps.
AMS Classification: 03E72, 97M99
References:
  1. Atanassov, K., Generalized index matrices, Comptes Rendus de l'Academie Bulgare des Sciences, Vol. 40, 1987, No. 11, 15-18.
  2. Atanassov, K., On index matrices, Part 1: Standard cases. Advanced Studies in Contemporary Mathematics, Vol. 20, 2010, No. 2, 291-302.
  3. Bureva V., E., Sotirova, K. Atanassov, New operations over intuitionistic fuzzy index matrices, Notes on Intuitionistic Fuzzy Sets, Vol. 18, 2012, No. 4, 12-18.
  4. Atanassov, K., Intuitionistic Fuzzy Sets: Theory and Applications, Springer Physica-Verlag, Berlin, 1999.
  5. Atanassov, K., On Intuitionistic Fuzzy Sets Theory, Studies in Fuzziness and Soft Computing, Vol. 283, Springer, Berlin, 2012.
  6. Reljin, I., B. Reljin, G.Jovanovic, Clustering and Mapping Spatial-Temporal Datasets Using SOM Neural Networks, Journal of Automatic Control, University of Belgrade, Vol. 13, 2003, No. 1, 55-60.
  7. Kohonen, T., Self-Organizing Maps. Series in Information Sciences, Vol.30, Springer, Heidelberg, 1995.
  8. Kohonen, T., J. Hynninen, J. Kangas, J. Laaksonen, SOM_PAK: The self-organizing map program package. Report A31. Helsinki University of Technology, Laboratory of Computer and Information Science, Espoo, Finland, 1996. [Available online at http://www.cis.hut.fi/research/som_lvq_pak.shtml.]
  9. Kaedi, M., M. Nematbakhsh, N. Ghasem-Aghaee, Fuzzy association rule reduction using clustering in SOM neural network, IADIS, European Conference Data Mining, 2008, 139–143.
  10. Mangiameli, P., S. K. Chen, D. West, A comparison of SOM neural network and hierarchical clustering methods, European Journal of Operational Research, Vol. 93, 1996, Issue 2, 402–417.
  11. Sotirova, E., S. Sotirov, I. Vardeva, B. Riečan, Publication’s assessment with intuitionistic fuzzy estimations, Notes on Intuitionistic Fuzzy Sets, Vol. 18, 2012, No. 4, 26–31.
  12. Sotirova, E., Classification of the students’ intuitionistic fuzzy estimations by a 3-dimensional self organizing map, Notes on Intuitionistic Fuzzy Sets, Vol. 17, 2011, No. 4, 64–68.
  13. Shannon, A., B. Riečan, E. Sotirova, M. Krawczak, K. Atanassov, P. Melo-Pinto, T. Kim, Modelling the process of PhD preparation using generalized nets, Proc. of 14th International Workshop on Generalized Nets, Burgas, 29–30 November 2013, 34–38.
  14. Shannon, A. G., Research degree supervision: ‘More mentor than master’, In: Postgraduate Studies, Postgraduate Pedagogy (Lee, A., B. Green, eds)., UTS, Sydney, 1998, 31–41.
  15. Trigwell, K., A. G. Shannon, R. Maurizi, Research-coursework Doctoral Programs in Australian Universities. Australian Government Publishing Service, Canberra, 1997.
Citations:

The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.