Title of paper:
|
Classification of the students' intuitionistic fuzzy estimations by a 3-dimensional self organizing map
|
Author(s):
|
Evdokia Sotirova
|
University “Prof. Asen Zlatarov”, 1 “Yakimov” Blvd., Burgas 8010, Bulgaria
|
esotirova@btu.bg
|
|
Presented at:
|
7th IWIFS, Banska Bystrica, 27 September 2011
|
Published in:
|
"Notes on IFS", Volume 17 (2011) Number 4, pages 39—44
|
Download:
|
PDF (85 Kb, File info)
|
Abstract:
|
The aim of the present paper is to use the techniques of self-organizing map (SOM) in the process of e-learning to assess the students’ knowledge on relevant topics in intuitionistic fuzzy form. The evaluation is formed on the basis of their answers. The self-organizing map is an effective tool for the visualization of high-dimensional data and its clustering. By clustering, students are classified into “similar” groups according to their intuitionistic fuzzy estimations. Thereby, a three-dimensional map for visualization of their knowledge in the intuitionistic fuzzy form is obtained.
|
Keywords:
|
Intuitionistic fuzzy sets, Self-organizing map, Clustering
|
AMS Classification:
|
03E72, 91C20
|
References:
|
- Atanassov, K. Generalized Nets, World Scientific, Singapore, 1991.
- Atanassov, K. On Generalized Nets Theory, “Prof. M. Drinov”Academic Publishing House, Sofia, 2007.
- Atanassov K., Intuitionistic Fuzzy Sets: Theory and Applications, Springer Physica-Verlag, Berlin, 1999.
- Atanassov K., Intuitionistic fuzzy sets. Fuzzy Sets and Systems, Vol. 20, 1986, 87–96.
- Freeman, A. Neural Network, Algorithms Applications and Programming Techniques. Addison Wesley, Reading, MA, 1991.
- Glenn, J. Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining. John Wiley, 2006.
- Reljin, I., B. Reljin, G. Jovanović, Clustering and mapping spatial-temporal datasets using SOM neural networks. Journal of Automatic Control, University of Belgrade; Vol. 13(1), 2003, 55–60.
- Kohonen, T. Self-Organizing Maps. Series in Information Sciences, Vol. 30. Springer, Heidelberg. 1995, Second ed. 1997.
- Kohonen, T., Hynninen, J., Kangas, J., Laaksonen, J. SOM_PAK: The self-organizing map program package. Report A31. Helsinki University of Technology, Laboratory of Computer and Information Science, Espoo, Finland, 1996.
- Kaedi, M., M. Nematbakhsh, N. Ghasem-Aghaee. Fuzzy Association Rule Reduction Using Clustering In SOM Neural Network, Proc. of IADIS, European Conference Data Mining, 2008, 139–143.
- Mangiameli, P., S. K. Chen, D. West, A comparison of SOM neural network and hier¬archical clustering methods. Neural Networks and Operations Research/ Management Science, European Journal of Operational Research, Vol. 93, Issue 2, 1996, 402–417.
- Wasserman, P. D., Neural computing, Theory and Practice. Van Nostrand Reinhold, New York, 1989.
- Sotirova, E., T. Petkov, S. Surchev, M. Krawczak. Generalized net model of Clustering with Self Organizing Map, Developments in Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets and Related Topics. Vol. 2: Applications Warsaw, Poland, 2011, 239–244.
- Sotirov, S., D. Orozova, E. Sotirova, Neural network for defining intuitionistic fuzzy sets in e-learning, Proc. of 13th Int. Conf. on Intuitionistic Fuzzy Sets, Sofia, NIFS Vol. 15, No. 2, 2009, 33–36.
- Sotirov, S., E. Sotirova, M. Krawczak, Application of data mining in digital university: multilayer perceptron for lecturer’s evaluation with intuitionistic fuzzy estimations, Issues in Intuitionistic Fuzzy Sets and Generalized Nets, Vol. 8, 2010, 102–107.
|
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.
|
|