Research Article
BibTex RIS Cite
Year 2018, Issue: 25, 84 - 102, 06.10.2018

Abstract

References

  • D. Molodtsov, Soft set theory-first results, Computers and Mathematics with Applications 37 (1999) 19-31.
  • P. K. Maji, R. Biswas, A. Roy, Fuzzy soft sets, The Journal of Fuzzy Mathematics 9 (3) (2001) 589-602.
  • P. K. Maji, A. Roy, R. Biswas, An application of soft sets in a decision making problem, Computers and Mathematics with Applications 44 (2002) 1077-1083.
  • P. K. Maji, R. Biswas, A. Roy, Soft set theory, Computers and Mathematics with Applications 45 (2003) 555-562.
  • N. Çağman, S. Enginoğlu, Soft set theory and uni-int decision making, European Journal of Operational Research 207 (2010) 848-855.
  • N. Çağman, S. Enginoğlu, Soft matrix theory and its decision making, Computers and Mathematics with Applications 59 (2010) 3308-3314.
  • 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.
  • N. Çağman, S. Enginoğlu, F. Çıtak, Fuzzy soft set theory and its applications, Iranian Journal of Fuzzy Systems 8 (3) (2011) 137-147.
  • N. Çağman, F. Çıtak, S. Enginoğlu, FP-soft set theory and its applications, Annals of Fuzzy Mathematics Information 2 (2) (2011) 219-226.
  • N. Çağman, S. Enginoğlu, Fuzzy soft matrix theory and its application in decision making, Iranian Journal of Fuzzy Systems 9 (1) (2012) 109-119.
  • S. Enginoğlu, Soft matrices, PhD thesis, Gaziosmanpasa University (2012).
  • S. Atmaca, İ. Zorlutuna, On topological structures of fuzzy parametrized soft sets, The Scientific World Journal 2014 (2014) Article ID 164176, 8 pages.
  • S. Enginoğlu, S. Karataş, N. Çağman, T. Aydın, On soft topology, El-Cezerî Journal of Science and Engineering 2 (3) (2015) 23-38.
  • F. Çıtak, N. Çağman, Soft int-rings and its algebraic applications, Journal of Intelligent and Fuzzy Systems 28 (2015) 1225-1233.
  • M. Tuncay, A. Sezgin, Soft union ring and its applications to ring theory, International Journal of Computer Applications 151 (9) (2016) 7-13.
  • F. Karaaslan, Soft classes and soft rough classes with applications in decision making, Mathematical Problems in Engineering 2016 (2016) Article ID 1584528, 11 pages.
  • İ. Zorlutuna, S. Atmaca, Fuzzy parametrized fuzzy soft topology, New Trends in Mathematical Sciences 4 (1) (2016) 142-152.
  • A. Sezgin, A new approach to semigroup theory I: Soft union semigroups, ideals and bi-ideals, Algebra Letters 2016 (2016) Article ID 3, 46 pages.
  • E. Muştuoğlu, A. Sezgin, Z. K. Türk, Some characterizations on soft uni-groups and normal soft uni-groups, International Journal of Computer Applications 155 (10) (2016) 8 pages.
  • S. Atmaca, Relationship between fuzzy soft topological spaces and (X,τ_e ) parameter spaces, Cumhuriyet Science Journal 38 (2017) 77-85.
  • S. Bera, S. K. Roy, F. Karaaslan, N. Çağman, Soft congruence relation over lattice, Hacettepe Journal of Mathematics and Statistics 46 (6) (2017) 1035-1042.
  • F. Çıtak, N. Çağman, Soft k-int-ideals of semirings and its algebraic structures, Annals of Fuzzy Mathematics and Informatics 13 (4) (2017) 531-538.
  • A. Ullah, F. Karaaslan, I. Ahmad, Soft uni-Abel-Grassmann's groups, European Journal of Pure and Applied Mathematics 11 (2) (2018) 517-536.
  • A. Sezgin, N. Çağman, F. Çıtak, α-inclusions applied to group theory via soft set and logic, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 68 (1) (2019) 334-352.
  • A. S. Razak, D. Mohamad, A soft set based group decision making method with criteria weight, World Academy of Science, Engineering and Technology 5 (10) (2011) 574-579.
  • S. Eraslan, A decision making method via topsis on soft sets, Journal of New Results in Science (8) (2015) 57-71.
  • A. S. Razak, D. Mohamad, A decision making method using fuzzy soft sets, Malaysian Journal of Fundamental and Applied Sciences 9 (2) (2013) 99-104.
  • P. K. Das, H. Borgohain, An application of fuzzy soft set in multicriteria decision making problem, International Journal of Computer Applications 38 (12) (2012) 33-37.
  • S. Eraslan, F. Karaaslan, A group decision making method based on topsis under fuzzy soft environment, Journal of New Theory (3) (2015) 30-40.
  • N. Çağman, İ. Deli, Means of FP-soft sets and their applications, Hacettepe Journal of Mathematics and Statistics 41 (5) (2012) 615-625.
  • K. Zhu, J. Zhan, Fuzzy parameterized fuzzy soft sets and decision making, International Journal of Machine Learning and Cybernetics 7 (2016) 1207-1212.
  • S. Vijayabalaji, A. Ramesh, A new decision making theory in soft matrices, International Journal of Pure and Applied Mathematics 86 (6) (2013) 927-939.
  • N. Khan, F. H. Khan, G. S. Thakur, Weighted fuzzy soft matrix theory and its decision making, International Journal of Advances in Computer Science and Technology 2 (10) (2013) 214-218.
  • S. Enginoğlu, S. Memiş, A configuration of some soft decision making algorithms via fpfs-matrices, Cumhuriyet Science Journal 39 (2018) xx-xx.
  • S. Enginoğlu, S. Memiş, B. Arslan, A fast and simple soft decision-making algorithm: EMA18an, International Conference on Mathematical Studies and Applications, Karaman, TURKEY, 2018.
  • 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. Subramanyam, C. 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.
  • K. Toh, N. Isa, Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter, Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction 17 (3) (2010) 281-284.
  • U. Erkan, L. Görkem, S. Enginoğlu, Different applied median filter in salt and pepper noise, Computers and Electrical Engineering 70 (2018) 789-798.
  • Z. Tang, K. Yang, K. Liu, Z. Pei, A new adaptive weighted mean filter for removing high density impulse noise, in: Eighth International Conference on Digital Image Processing (ICDIP 2016), Vol. 10033, International Society for Optics and Photonics, 2016, pp. 1003353/1-5.
  • W. Zhou, H. Bovik, E. Simoncelli, Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing 13 (4) (2004) 600-612.

Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research

Year 2018, Issue: 25, 84 - 102, 06.10.2018

Abstract

The
uni-int decision-making method, which selects a set of optimum elements from
the alternatives, was defined by Çağman and Enginoğlu via soft sets and their
soft products. Lately, this method constructed by and-product/or-product has
been configured by Enginoğlu and Memiş via fuzzy parameterized fuzzy soft
matrices (fpfs-matrices), faithfully to the original, because a more general
form is needed for the method in the event that the parameters or objects have
uncertainties. In this study, we configure the method via fpfs-matrices and
andnot-product/ornot-product, faithfully to the original. However, in the case
that a large amount of data is processed, the method still has a disadvantage
regarding time and complexity. To deal with this problem and to be able to use
this configured method effectively denoted by CE10, we suggest two new
algorithms in this paper, i.e. EMA18an and EMA18on, and prove that CE10
constructed by andnot-product (CE10an) and constructed by ornot-product
(CE10on) are special cases of EMA18an and EMA18on, respectively, if first rows
of the fpfs-matrices are binary. We then compare the running times of these
algorithms. The results show that EMA18an and EMA18on outperform CE10an and
CE10on, respectively. Particularly in problems containing a large amount of
parameters, EMA18an and EMA18on offer up to 99.9966% and 99.9964% of time
advantage, respectively. Latterly, we apply EMA18on to a performance-based
value assignment to the methods used in noise removal, so that we can order
them in terms of performance. Finally, we discuss the need for further
research.

References

  • D. Molodtsov, Soft set theory-first results, Computers and Mathematics with Applications 37 (1999) 19-31.
  • P. K. Maji, R. Biswas, A. Roy, Fuzzy soft sets, The Journal of Fuzzy Mathematics 9 (3) (2001) 589-602.
  • P. K. Maji, A. Roy, R. Biswas, An application of soft sets in a decision making problem, Computers and Mathematics with Applications 44 (2002) 1077-1083.
  • P. K. Maji, R. Biswas, A. Roy, Soft set theory, Computers and Mathematics with Applications 45 (2003) 555-562.
  • N. Çağman, S. Enginoğlu, Soft set theory and uni-int decision making, European Journal of Operational Research 207 (2010) 848-855.
  • N. Çağman, S. Enginoğlu, Soft matrix theory and its decision making, Computers and Mathematics with Applications 59 (2010) 3308-3314.
  • 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.
  • N. Çağman, S. Enginoğlu, F. Çıtak, Fuzzy soft set theory and its applications, Iranian Journal of Fuzzy Systems 8 (3) (2011) 137-147.
  • N. Çağman, F. Çıtak, S. Enginoğlu, FP-soft set theory and its applications, Annals of Fuzzy Mathematics Information 2 (2) (2011) 219-226.
  • N. Çağman, S. Enginoğlu, Fuzzy soft matrix theory and its application in decision making, Iranian Journal of Fuzzy Systems 9 (1) (2012) 109-119.
  • S. Enginoğlu, Soft matrices, PhD thesis, Gaziosmanpasa University (2012).
  • S. Atmaca, İ. Zorlutuna, On topological structures of fuzzy parametrized soft sets, The Scientific World Journal 2014 (2014) Article ID 164176, 8 pages.
  • S. Enginoğlu, S. Karataş, N. Çağman, T. Aydın, On soft topology, El-Cezerî Journal of Science and Engineering 2 (3) (2015) 23-38.
  • F. Çıtak, N. Çağman, Soft int-rings and its algebraic applications, Journal of Intelligent and Fuzzy Systems 28 (2015) 1225-1233.
  • M. Tuncay, A. Sezgin, Soft union ring and its applications to ring theory, International Journal of Computer Applications 151 (9) (2016) 7-13.
  • F. Karaaslan, Soft classes and soft rough classes with applications in decision making, Mathematical Problems in Engineering 2016 (2016) Article ID 1584528, 11 pages.
  • İ. Zorlutuna, S. Atmaca, Fuzzy parametrized fuzzy soft topology, New Trends in Mathematical Sciences 4 (1) (2016) 142-152.
  • A. Sezgin, A new approach to semigroup theory I: Soft union semigroups, ideals and bi-ideals, Algebra Letters 2016 (2016) Article ID 3, 46 pages.
  • E. Muştuoğlu, A. Sezgin, Z. K. Türk, Some characterizations on soft uni-groups and normal soft uni-groups, International Journal of Computer Applications 155 (10) (2016) 8 pages.
  • S. Atmaca, Relationship between fuzzy soft topological spaces and (X,τ_e ) parameter spaces, Cumhuriyet Science Journal 38 (2017) 77-85.
  • S. Bera, S. K. Roy, F. Karaaslan, N. Çağman, Soft congruence relation over lattice, Hacettepe Journal of Mathematics and Statistics 46 (6) (2017) 1035-1042.
  • F. Çıtak, N. Çağman, Soft k-int-ideals of semirings and its algebraic structures, Annals of Fuzzy Mathematics and Informatics 13 (4) (2017) 531-538.
  • A. Ullah, F. Karaaslan, I. Ahmad, Soft uni-Abel-Grassmann's groups, European Journal of Pure and Applied Mathematics 11 (2) (2018) 517-536.
  • A. Sezgin, N. Çağman, F. Çıtak, α-inclusions applied to group theory via soft set and logic, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 68 (1) (2019) 334-352.
  • A. S. Razak, D. Mohamad, A soft set based group decision making method with criteria weight, World Academy of Science, Engineering and Technology 5 (10) (2011) 574-579.
  • S. Eraslan, A decision making method via topsis on soft sets, Journal of New Results in Science (8) (2015) 57-71.
  • A. S. Razak, D. Mohamad, A decision making method using fuzzy soft sets, Malaysian Journal of Fundamental and Applied Sciences 9 (2) (2013) 99-104.
  • P. K. Das, H. Borgohain, An application of fuzzy soft set in multicriteria decision making problem, International Journal of Computer Applications 38 (12) (2012) 33-37.
  • S. Eraslan, F. Karaaslan, A group decision making method based on topsis under fuzzy soft environment, Journal of New Theory (3) (2015) 30-40.
  • N. Çağman, İ. Deli, Means of FP-soft sets and their applications, Hacettepe Journal of Mathematics and Statistics 41 (5) (2012) 615-625.
  • K. Zhu, J. Zhan, Fuzzy parameterized fuzzy soft sets and decision making, International Journal of Machine Learning and Cybernetics 7 (2016) 1207-1212.
  • S. Vijayabalaji, A. Ramesh, A new decision making theory in soft matrices, International Journal of Pure and Applied Mathematics 86 (6) (2013) 927-939.
  • N. Khan, F. H. Khan, G. S. Thakur, Weighted fuzzy soft matrix theory and its decision making, International Journal of Advances in Computer Science and Technology 2 (10) (2013) 214-218.
  • S. Enginoğlu, S. Memiş, A configuration of some soft decision making algorithms via fpfs-matrices, Cumhuriyet Science Journal 39 (2018) xx-xx.
  • S. Enginoğlu, S. Memiş, B. Arslan, A fast and simple soft decision-making algorithm: EMA18an, International Conference on Mathematical Studies and Applications, Karaman, TURKEY, 2018.
  • 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. Subramanyam, C. 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.
  • K. Toh, N. Isa, Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter, Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction 17 (3) (2010) 281-284.
  • U. Erkan, L. Görkem, S. Enginoğlu, Different applied median filter in salt and pepper noise, Computers and Electrical Engineering 70 (2018) 789-798.
  • Z. Tang, K. Yang, K. Liu, Z. Pei, A new adaptive weighted mean filter for removing high density impulse noise, in: Eighth International Conference on Digital Image Processing (ICDIP 2016), Vol. 10033, International Society for Optics and Photonics, 2016, pp. 1003353/1-5.
  • W. Zhou, H. Bovik, E. Simoncelli, Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing 13 (4) (2004) 600-612.
There are 41 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Research Article
Authors

Serdar Enginoğlu 0000-0002-7188-9893

Samet Memiş 0000-0002-0958-5872

Burak Arslan 0000-0002-1724-8841

Publication Date October 6, 2018
Submission Date November 14, 2018
Published in Issue Year 2018 Issue: 25

Cite

APA Enginoğlu, S., Memiş, S., & Arslan, B. (2018). Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research. Journal of New Theory(25), 84-102.
AMA Enginoğlu S, Memiş S, Arslan B. Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research. JNT. October 2018;(25):84-102.
Chicago Enginoğlu, Serdar, Samet Memiş, and Burak Arslan. “Comment (2) on Soft Set Theory and Uni-Int Decision Making [European Journal of Operational Research”. Journal of New Theory, no. 25 (October 2018): 84-102.
EndNote Enginoğlu S, Memiş S, Arslan B (October 1, 2018) Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research. Journal of New Theory 25 84–102.
IEEE S. Enginoğlu, S. Memiş, and B. Arslan, “Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research”, JNT, no. 25, pp. 84–102, October 2018.
ISNAD Enginoğlu, Serdar et al. “Comment (2) on Soft Set Theory and Uni-Int Decision Making [European Journal of Operational Research”. Journal of New Theory 25 (October 2018), 84-102.
JAMA Enginoğlu S, Memiş S, Arslan B. Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research. JNT. 2018;:84–102.
MLA Enginoğlu, Serdar et al. “Comment (2) on Soft Set Theory and Uni-Int Decision Making [European Journal of Operational Research”. Journal of New Theory, no. 25, 2018, pp. 84-102.
Vancouver Enginoğlu S, Memiş S, Arslan B. Comment (2) on Soft Set Theory and uni-int Decision Making [European Journal of Operational Research. JNT. 2018(25):84-102.


TR Dizin 26024

Electronic Journals Library (EZB) 13651



Academindex 28993

SOBİAD 30256                                                   

Scilit 20865                                                  


29324 As of 2021, JNT is licensed under a Creative Commons Attribution-NonCommercial 4.0 International Licence (CC BY-NC).