CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory

by Omdutt Sharma, Prince Goyal, Priti Gupta
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 2
Year of Publication: 2017
Authors: Omdutt Sharma, Prince Goyal, Priti Gupta
10.5120/ijca2017915490

Omdutt Sharma, Prince Goyal, Priti Gupta . An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory. International Journal of Computer Applications. 175, 2 ( Oct 2017), 17-25. DOI=10.5120/ijca2017915490

@article{ 10.5120/ijca2017915490,
author = { Omdutt Sharma, Prince Goyal, Priti Gupta },
title = { An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2017 },
volume = { 175 },
number = { 2 },
month = { Oct },
year = { 2017 },
issn = { 0975-8887 },
pages = { 17-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number2/28460-2017915490/ },
doi = { 10.5120/ijca2017915490 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:23:58.727721+05:30
%A Omdutt Sharma
%A Prince Goyal
%A Priti Gupta
%T An Approach to Data Reduction and Decision Making Problem by Hybridization of Fuzzy Soft Set and Graph Theory
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 2
%P 17-25
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To deal with the uncertainties present in real life situations both fuzzy set and soft set approach are concerned. But these approaches have some challenges, to solve related dilemma a hybridization approach is operated known as fuzzy soft set approach, which is the hybridization of fuzzy sets and soft set theory. Graph theory is also a significant tactic to solve some existent problem graphically. In this paper, a brief study of fuzzy soft sets and graph theory are done. Here a definition of fuzzy soft graph is defined and give a method to solve decision making problem and data reduction problem by using fuzzy soft set definition defined by us. At last discuss an application of decision making and data reduction problem by using fuzzy soft sets and graph theory.

References
  1. Zadeh, L. A. 1965. Fuzzy sets, Information and Control 8, 338-353, ().
  2. Molodtsov, D. 1999. Soft set theory- first results, Computers Math. Applic. 37 (4/5), 19-31.
  3. Maji, P. K., Roy, A. R. & Biswas, R. 2001. Fuzzy soft sets, The Journal of fuzzy mathematics, ((3), 589-602.
  4. Maji, P. K., Roy, A. R. & Biswas, R. 2002. An application of soft sets in a decision making Problem, Computer and Mathematics with application, 44, 1077-1083.
  5. Maji, P. K., Roy, A. R. & Biswas, R. 2003. Soft set theory, Computers and Mathematics with Applications, 45, 555-562.
  6. Roy, A.R. & Maji, P. K. 2007. A fuzzy soft set theoretic approach to decision making problems”. J. Comput. Appl. Math., 203, 412-418.
  7. Chen, D., Tsang, E. C. C., Yeung, D. S. & Wang, X. 2005. The parameterization reduction of soft sets and its applications, Computers and mathematics with applications, 49, 757-763.
  8. Gupta, P. & Sharma, O. D. (2015). Feature Selection: An Overview, Impact: International Journal of Information Engineering and Technology, 1, 1- 12.
  9. Rosenfeld, A. 1975. Fuzzy graphs, Fuzzy sets and their applications, (L. A. Zadeh, K. S. Fu, M. Shimura, Eds) Academic Press, New York, 77-95.
  10. Thumbakara, R. K. & George, B. 2014. Soft graphs, Gen. Math. Notes, vol. 21, no. 2, pp. 75-86, ICSRS Publication.
  11. Mohinta, S. & Samanta, T. K. 2015. An introduction to fuzzy soft graph, MathematicaMoravica, vol. 19-2, 35-48.
  12. Thomas, D. G. & Arockiarani, I. 2013. Decision making via Soft graphs, International Journal of Mathematical Archive- 4(6), 50-55.
  13. Zou, Y. & Xiao, Z. 2008. Data analysis approach of soft sets under incomplete information, Knowl. Base Syst., 21, 941-945.
  14. Yang, X., Lin, T. Y., Yang, J., Li, Y. and Yu, D. (2009). Combination of interval-valued fuzzy set and soft set, Comput. Math. Appl., 58, 521-527.
  15. Kong, Z., Gao, L., Wang, L. and Li, S. 2008. The normal parameter reduction of soft set and its algorithm, Comput. Math. Appl., 56, 3029-3037.
  16. Kong, Z., Gao, L. & Wang, L. 2009. Comment On “ A fuzzy soft set theoretic approach to decision making problems”, J. Comput. Appl. Math., 223, 540-542.
  17. Akram, M. & Nawaz, S. 2015. On Fuzzy Soft Graphs, Italian Journal of Pure and Applied Mathematics, 34, 497-514, 9.
  18. Akram, M. & Nawaz, S. 2015. Operatiom on Soft Graphs, Fuzzy information and Engineering, 7, 423-449.
  19. Sharma, O., Gupta, P. & Abhishek, A novel approach of dimensionality reduction by fuzzy soft set (Communicated).
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy set soft set fuzzy soft set graph theory soft graph fuzzy soft graph feature selection decision making.

Powered by PhDFocusTM