Image Mining Inranking Approach under Interval-Valued Hesitant Fuzzy Set Gr Selection

Authors(1) :-Prof P. Senthil

In the last decades, considerations concerning the environmental problems cause skilled and educational efforts on inexperienced provider choice issues. during this sake, one among the most problems in evaluating the inexperienced provider choice issues, that might increase the uncertainty, is that the preferences of the experts' judgments concerning the candidate inexperienced suppliers. Therefore, getting ready AN professional system to guage the matter supported the historical information and therefore the experts' data are often smart. Image Mining provides AN professional analysis system to assess the candidate inexperienced suppliers underneath chosen criteria in an exceedingly multi-period approach. additionally, a ranking approach underneath interval-valued hesitant fuzzy set (IVHFS) setting is projected to pick the foremost acceptable inexperienced provider in designing horizon. within the projected ranking approach, the IVHFS and therefore the last aggregation approach is taken into account to margin the errors and to forestall information loss, severally. Hence, a comparative ANalysis is provided supported an illustrative example to point out the feasibleness of the projected approach.

Authors and Affiliations

Prof P. Senthil
Department of Computer Science, Kurinji College of Arts and Science, Tiruchirappalli Tamil Nadu, India

Green selection, Expert system, Ranking approach, Interval-valued hesitant fuzzy setting,Image Mining

  1. Yu, D.J. Triangular Atanassov’s intuitionistic fuzzy Bonferroni mean and application to supplier selection.J. Intell. Fuzzy Syst. 2015, 28, 2785–2791.
  2. Yu, D.J. Intuitionistic fuzzy geometric Heronian mean aggregation operators. Appl. Soft Comput. 2013, 13,1235–1246.
  3. Yager, R.R. On generalized Bonferroni mean operators for multi-criteria aggregation. Int. J. Approx. Reason.2009, 50, 1279–1286.
  4. Verma, R. Generalized Bonferroni mean operator for fuzzy number intuitionistic fuzzy sets and its application to multi-attribute decision making. Int. J. Intell. Syst. 2015, 30, 499–519.
  5. Gong, Y.; Hu, N.; Zhang, J.; Liu, G.; Deng, J. Multi-attribute group decision making method based on geometric Bonferroni mean operator of trapezoidal interval type-2 fuzzy numbers. Comput. Ind. Eng. 2015,81, 167–176.
  6. He, Y.D.; He, Z.; Chen, H.Y. Intuitionistic fuzzy interaction Bonferroni means and its application to multiple attribute decision making. IEEE Trans. Cybern. 2015, 45, 116–128.
  7. Xu, Z.S.; Yager, R.R. Intuitionistic fuzzy Bonferroni means. IEEE Trans. Syst. Man Cybern. Part B Cybern. 2011,41, 568–578.
  8. Yu, D.J. Intuitionistic fuzzy theory based typhoon disaster evaluation in Zhejiang Province, China:A comparative perspective. Nat. Hazards 2015, 75, 2559–2576.
  9. Yu, D.J. A scientometrics review on aggregation operator research. Scientometrics 2015, 105, 115–133.
  10. Yu, D.J.; Shi, S.S. Researching the development of Atanassov intuitionistic fuzzy set: Using a citation network analysis. Appl. Soft Comput. 2015, 32, 189–198.
  11. Xia, M.M.; Xu, Z.S.; Zhu, B. Generalized intuitionistic fuzzy Bonferroni means. Int. J. Intell. Syst. 2012, 27,23–47.
  12. Xu, Z.S.; Chen, Q. A multi-criteria decision making procedure based on interval-valued intuitionistic fuzzy bonferroni means. J. Syst. Sci. Syst. Eng. 2011, 20, 217–228.
  13. Zhu, B.; Xu, Z.S. Hesitant fuzzy Bonferroni means for multi-criteria decision making. J. Oper. Res. Soc. 2013,1831–1840.
  14. Zhu, B.; Xu, Z.S.; Xia, M.M. Hesitant fuzzy geometric Bonferroni means. Inf. Sci. 2012, 205, 72–85.
  15. Chen, N.; Xu, Z.; Xia, M. Interval-valued hesitant preference relations and their applications to group decision making. Knowl.-Based Syst. 2013, 37, 528–540.
  16. Wei, G.; Zhao, X.; Lin, R. Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making. Knowl.-Based Syst. 2013, 46, 43–53.
  17. Wei, G.; Zhao, X. Induced hesitant interval-valued fuzzy Einstein aggregation operators and their application to multiple attribute decision making. J. Intell. Fuzzy Syst. 2013, 24, 789–803.
  18. Wei, G.W.; Alsaadi, F.E.; Hayat, T.; Alsaedi, A. A linear assignment method for multiple criteria decision analysis with hesitant fuzzy sets based on fuzzy measure. Int. J. Fuzzy Syst. 2016, 1–8.
  19. Yu, D.J. Group decision making under interval-valued multiplicative intuitionistic fuzzy environment based on Archimedean t-conorm and t-norm. Int. J. Intell. Syst. 2015, 30, 590–616.
  20. Yu, D.J.; Zhang, W.Y.; Huang, G. Dual hesitant fuzzy aggregation operators. Technol. Econ. Dev. Econ. 2015,22, 1–16.
  21. He, X.R.; Wu, Y.Y.; Yu, D.J. Intuitionistic fuzzy multi-criteria decision making with application to job hunting:A comparative perspective. J. Intell. Fuzzy Syst. 2016, 30, 1935–1946.
  22. Senthil P. IMAGE MINING CLASSIFICATION MRI SCAN USED BRAIN TUMOR ANALYSIS (IMICLA). Journal of Computer - JoC. 2016 Jul 22;1(Volume 1 Issue 1 ISSN:2518-6205):21-35.
  23. Senthil P. IMAGE MINING USED SEGMENTATION TECHNIQUE MRI SCAN BRAIN TUMOR IMAGES ANALYSIS (IMUSA). Journal of Computer - JoC, Available Online at: 2016 Jul 22;1(Volume 1 Issue 1 ISSN:2518-6205):36-50.
  24. Senthil P. Image Mining in Tumor Detection in Brain using Sushisen in Arima Model. Indian Journal Of Natural Sciences. 2016 Sep 3;37(1):Pages-11480.
  25. Senthil P. Image Mining in Fuzzy Model Approaches Based Random walker algorithm Brain Tumor Analysis (Meningioma Analysis). International Journal of Computer Science & Engineering Technology (IJCSET). 2016 Aug 1;7(Vol. 7 No. 07 Jul 2016):Pages-303.

Publication Details

Published in : Volume 1 | Issue 2 | September-October 2016
Date of Publication : 2016-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 105-114
Manuscript Number : CSEIT161216
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Prof P. Senthil, "Image Mining Inranking Approach under Interval-Valued Hesitant Fuzzy Set Gr Selection", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 1, Issue 2, pp.105-114, September-October-2016.
Journal URL :

Article Preview