Research Article
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Year 2019, Issue: 29, 79 - 88, 30.12.2019

Emre Sulukan Naim Cagman Tuğçe Aydın

Abstract

References

  • L. A. Zadeh, Fuzzy Sets, Information and Control 8(3) (1965) 338-353.
  • K. T. Atanassov, Intuitionistic Fuzzy Sets, Fuzzy Sets and Systems 20(1) (1986) 87-96.
  • D. A. Molodtsov, Soft Set Theory-First Results, Computers and Mathematics with Applications 37(4-5) (1999) 19-31.
  • P. K. Maji, R. Biswas, A. R. Roy, Fuzzy Soft Sets, Journal of Fuzzy Mathematics 9(3) (2001) 589-602.
  • P. K. Maji, R. Biswas, A. R. Roy, Intuitionistic Fuzzy Soft Sets, The Journal of Fuzzy Mathematics 9(3) (2001) 677-692.
  • N. Çağman, F. Çıtak, S. Enginoğlu, FP-Soft Set Theory and Its Applications, Annals of Fuzzy Mathematics and Informatics 2(2) (2011) 219-226.
  • N. Çağman, F. Çıtak, S. Enginoğlu, Fuzzy Parameterized Fuzzy Soft Set Theory and Its Applications, Turkish Journal of Fuzzy Systems 1(1) (2010) 21-35.
  • İ. Deli, N. Çağman, Intuitionistic Fuzzy Parameterized Soft Set Theory and Its Decision Making, Applied Soft Computing 28 (2015) 109-113.
  • E. El-Yagubi, A. R. Salleh, Intuitionistic Fuzzy Parameterised Fuzzy Soft Set, Journal of Quality Measurement and Analysis 9(2) (2013) 73-81.
  • F. Karaaslan, Intuitionistic Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets with Applications in Decision Making, Annals of Fuzzy Mathematics and Informatics 11(4) (2016) 607-619.
  • N. Çağman, S. Enginoğlu, Soft Set Theory and uni-int Decision Making, European Journal of Operational Research 207(2) (2010) 848-855.
  • P. K. Maji, R. Biswas, A. R. Roy, Soft Set Theory, Computers and Mathematics with Applications 45(4-5) (2003) 555-562.
  • D. Dubois, H. Prade, Fuzzy Set and Systems: Theory and Applications, Academic Press, New York, 1980.
  • G. J. Klir, T. A. Folger, Fuzzy Sets, Uncertainty and Information, Prentice-Hall, 1988.
  • H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Kluwer, 1991.
  • K. T. Atanassov, Intuitionistic Fuzzy Sets Theory and Applications, Physica-Verlag Heidelberg, 1999.
  • Q. Lei, Z. Xu, Intuitionistic Fuzzy Calculus, Springer, 2017.
  • A. Pattnaik, S. Agarwal, S. Chand, A New and Efficient Method for Removal of High Density Salt and Pepper Noise through Cascade Decision Based Filtering Algorithm, Procedia Technology 6 (2012) 108-117.
  • S. Esakkirajan, T. Veerakumar, A. N. Subramanyam, C. H. PremChand, Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter, IEEE Signal Processing Letters 18(5) (2011) 287-290.
  • U. Erkan, L. Gökrem, A New Method Based on Pixel Density in Salt and Pepper Noise Removal, Turkish Journal of Electrical Engineering and Computer Sciences 26(1) (2018) 162-171.
  • K. K. V. Toh, N. A. M. Isa, Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction, IEEE Signal Processing Letters 17(3) (2010) 281-284.
  • Z. Tang, K. Yang, K. Liu, Z. Pei, A New Adaptive Weighted Mean Filter for Removing High Density Impulse Noise, SPIE Proceedings, Eighth International Conference on Digital Image Processing (ICDIP 2016), International Society for Optics and Photonics 10033 (2016) 1003353/1-5.
  • U. Erkan, L. Gökrem, S. Enginoğlu, Different Applied Median Filter in Salt and Pepper Noise, Computers and Electrical Engineering 70 (2018) 789-798.
  • S. Enginoğlu, U. Erkan, S. Memiş, Pixel Similarity-Based Adaptive Riesz Mean Filter for Salt-and-Pepper Noise Removal, Multimedia Tools and Applications 78 (2019) 35401-35418.
  • Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing 13(4) (2004) 600-612.

Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem

Year 2019, Issue: 29, 79 - 88, 30.12.2019

Emre Sulukan Naim Cagman Tuğçe Aydın

Abstract

Soft sets have been successfully applied to many different fields to cope with uncertainties. Recently, to increase the success of the applications, these sets have been combined with other theories, such as fuzzy sets and intuitionistic fuzzy sets. In this study, we propose the concept of fuzzy parameterized intuitionistic fuzzy soft sets (fpifs-sets). We then apply these sets to a performance-based value assignment (PVA) problem. Finally, we give suggestions for further research.

Keywords

Fuzzy sets intuitionistic fuzzy sets soft sets intuitionistic fuzzy soft sets fpifs-sets

References

  • L. A. Zadeh, Fuzzy Sets, Information and Control 8(3) (1965) 338-353.
  • K. T. Atanassov, Intuitionistic Fuzzy Sets, Fuzzy Sets and Systems 20(1) (1986) 87-96.
  • D. A. Molodtsov, Soft Set Theory-First Results, Computers and Mathematics with Applications 37(4-5) (1999) 19-31.
  • P. K. Maji, R. Biswas, A. R. Roy, Fuzzy Soft Sets, Journal of Fuzzy Mathematics 9(3) (2001) 589-602.
  • P. K. Maji, R. Biswas, A. R. Roy, Intuitionistic Fuzzy Soft Sets, The Journal of Fuzzy Mathematics 9(3) (2001) 677-692.
  • N. Çağman, F. Çıtak, S. Enginoğlu, FP-Soft Set Theory and Its Applications, Annals of Fuzzy Mathematics and Informatics 2(2) (2011) 219-226.
  • N. Çağman, F. Çıtak, S. Enginoğlu, Fuzzy Parameterized Fuzzy Soft Set Theory and Its Applications, Turkish Journal of Fuzzy Systems 1(1) (2010) 21-35.
  • İ. Deli, N. Çağman, Intuitionistic Fuzzy Parameterized Soft Set Theory and Its Decision Making, Applied Soft Computing 28 (2015) 109-113.
  • E. El-Yagubi, A. R. Salleh, Intuitionistic Fuzzy Parameterised Fuzzy Soft Set, Journal of Quality Measurement and Analysis 9(2) (2013) 73-81.
  • F. Karaaslan, Intuitionistic Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets with Applications in Decision Making, Annals of Fuzzy Mathematics and Informatics 11(4) (2016) 607-619.
  • N. Çağman, S. Enginoğlu, Soft Set Theory and uni-int Decision Making, European Journal of Operational Research 207(2) (2010) 848-855.
  • P. K. Maji, R. Biswas, A. R. Roy, Soft Set Theory, Computers and Mathematics with Applications 45(4-5) (2003) 555-562.
  • D. Dubois, H. Prade, Fuzzy Set and Systems: Theory and Applications, Academic Press, New York, 1980.
  • G. J. Klir, T. A. Folger, Fuzzy Sets, Uncertainty and Information, Prentice-Hall, 1988.
  • H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Kluwer, 1991.
  • K. T. Atanassov, Intuitionistic Fuzzy Sets Theory and Applications, Physica-Verlag Heidelberg, 1999.
  • Q. Lei, Z. Xu, Intuitionistic Fuzzy Calculus, Springer, 2017.
  • A. Pattnaik, S. Agarwal, S. Chand, A New and Efficient Method for Removal of High Density Salt and Pepper Noise through Cascade Decision Based Filtering Algorithm, Procedia Technology 6 (2012) 108-117.
  • S. Esakkirajan, T. Veerakumar, A. N. Subramanyam, C. H. PremChand, Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter, IEEE Signal Processing Letters 18(5) (2011) 287-290.
  • U. Erkan, L. Gökrem, A New Method Based on Pixel Density in Salt and Pepper Noise Removal, Turkish Journal of Electrical Engineering and Computer Sciences 26(1) (2018) 162-171.
  • K. K. V. Toh, N. A. M. Isa, Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction, IEEE Signal Processing Letters 17(3) (2010) 281-284.
  • Z. Tang, K. Yang, K. Liu, Z. Pei, A New Adaptive Weighted Mean Filter for Removing High Density Impulse Noise, SPIE Proceedings, Eighth International Conference on Digital Image Processing (ICDIP 2016), International Society for Optics and Photonics 10033 (2016) 1003353/1-5.
  • U. Erkan, L. Gökrem, S. Enginoğlu, Different Applied Median Filter in Salt and Pepper Noise, Computers and Electrical Engineering 70 (2018) 789-798.
  • S. Enginoğlu, U. Erkan, S. Memiş, Pixel Similarity-Based Adaptive Riesz Mean Filter for Salt-and-Pepper Noise Removal, Multimedia Tools and Applications 78 (2019) 35401-35418.
  • Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing 13(4) (2004) 600-612.
There are 25 citations in total.

Details

Primary Language English
Subjects Applied Mathematics
Journal Section Research Article
Authors

Emre Sulukan This is me

Naim Cagman

Tuğçe Aydın

Publication Date December 30, 2019
Submission Date December 6, 2019
Published in Issue Year 2019 Issue: 29

Cite

APA Sulukan, E., Cagman, N., & Aydın, T. (2019). Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem. Journal of New Theory(29), 79-88.
AMA Sulukan E, Cagman N, Aydın T. Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem. JNT. December 2019;(29):79-88.
Chicago Sulukan, Emre, Naim Cagman, and Tuğçe Aydın. “Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem”. Journal of New Theory, no. 29 (December 2019): 79-88.
EndNote Sulukan E, Cagman N, Aydın T (December 1, 2019) Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem. Journal of New Theory 29 79–88.
IEEE E. Sulukan, N. Cagman, and T. Aydın, “Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem”, JNT, no. 29, pp. 79–88, December 2019.
ISNAD Sulukan, Emre et al. “Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem”. Journal of New Theory 29 (December 2019), 79-88.
JAMA Sulukan E, Cagman N, Aydın T. Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem. JNT. 2019;:79–88.
MLA Sulukan, Emre et al. “Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem”. Journal of New Theory, no. 29, 2019, pp. 79-88.
Vancouver Sulukan E, Cagman N, Aydın T. Fuzzy Parameterized Intuitionistic Fuzzy Soft Sets and Their Application to a Performance-Based Value Assignment Problem. JNT. 2019(29):79-88.
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