Random Articles
Reseach Article
A Comparative Study of Fuzzy and Intuitionistic Fuzzy Techniques in a Knowledge based Decision Support
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 53 - Number 7 |
| Year of Publication: 2012 |
| Authors: Asma R Shora, M Afshar Alam, Ranjit Biswas |
10.5120/8433-2205
|
Asma R Shora, M Afshar Alam, Ranjit Biswas . A Comparative Study of Fuzzy and Intuitionistic Fuzzy Techniques in a Knowledge based Decision Support. International Journal of Computer Applications. 53, 7 ( September 2012), 13-16. DOI=10.5120/8433-2205
Abstract
Through this paper we present the implementation of fuzzy decision making in case of a medical diagnostic system and compare the results with those of the Intuitionistic fuzzy decision making technique. Both the approaches are used to solve multi-criteria, complex decision making problems. Intuitionistic fuzzy differs from the fuzzy approach as it adds indeterminacy and imprecision to the fuzzy technology. Let us consider a simple diagnostic system where we diagnose the causes of obesity. Patients are treated for obesity according to the type of obesity they have or let us say the cause of their obesity. Obesity can be lifestyle related or it can be a pathological or genetic disorder. Both fuzzy and Intuitionistic fuzzy techniques will determine the cause of obesity. It is for us to decide which one is the efficient way to do it.
References
- Asma R Shora , Afshar Alam, Tamanna Sidiqui, (2012) Knowledge-driven Intuitionistic Fuzzy Decision Support for finding out the causes of Obesity, IJCSE Volume 4 Issue 3
- Fatih Emre Boran (2011) An integrated intuitionistic fuzzy multicriteria decision making method for facility location selection, Mathematical and Computational Applications, (Vol. 16, No. 2, pp. 487-496, 2011. ).
- Chris Cornelis, E. E. Kerre(2001). Inclusion based approximate reasoning. In lecture notes in Computer Science 2074(V. Alexendrov, J. Dongarra, B. Julliano, R Renner, C. Tan, eds. ), Springer-Verlag ,pages 200-210.
- S. Parsons, "Current approaches to handling imperfect information in data and knowledge bases," IEEE Transactions on Knowledge and Data Engineering, Vol. 8, 1996, pp. 353-372
- Cecilia Temponi, Anthony Shannon, Krassimir Atanassov, Adrian Ban (1999), An idea for an Intuitionistic Fuzzy approach to decision making, Third Int. conf on IFS, Sofia,16-17 October 1999, Notes on IFS, Volume 5 (1999) Number 3, page 6-10.
- E. E. Kerre and G. Q. Chen, "An overview of fuzzy data modeling," Fuzziness in Database Management Systems, Physica-Verlag, 1995, pp. 23-41
- K T Attanasov (1999) Intuitionistic Fuzzy sets, Physica- Verlag, Heidelberg, NewYork.
- C. Cornelis, E. E Kerre (2002). A Fuzzy Inference methodology based on the Fuzzification of set inclusion. In Innovations in Intelligent Systems(A. Abrahim , B. Nath, eds. ), studies in Fuzziness and Soft computing series, Springer –Verlag.
- Buckles, B. P. and Petry F. E. , A fuzzy representation of data for relational databases, Fuzzy sets and Systems 7(3) (1982) 213-226.
- Baoding Liu (2012), Membership functions and operational law of uncertain sets, Fuzzy Optimization and Decision Making, Springer.
- F. Herrera, S. Alonso, F. Chiclana and E. Herrera- Viedma, Computing with words in decision making: foundations, trends and prospects ,From the issue entitled "Special Issue: Computing with Words and Decision Making", Fuzzy Optimization and Decision Making ,Springer
Index Terms
Keywords