The circular intuitionistic fuzzy set (CIFS) extends the concept of IFS, representing each set element with a circular area on the IFS interpretation triangle (IFIT). Each element in CIFS is characterized not only by membership and non-membership degrees but also by a radius, indicating the imprecise areas of these degrees. While some basic operations have been defined for CIFS, not all have been thoroughly explored and generalized. The radius domain has been extended from $ [0, 1] $ to $ [0, \sqrt{2}] $. However, the operations on the radius domain are limited to $ min $ and $ max $. We aimed to address these limitations and further explore the theory of CIFS, focusing on operations for membership and non-membership degrees as well as radius domains. First, we proposed new radius operations on CIFS with a domain $ [0, \psi] $, where $ \psi \in [1, \sqrt{2}] $, called a radius algebraic product (RAP) and radius algebraic sum (RAS). Second, we developed basic operators for generalized union and intersection operations on CIFS based on triangular norms and conorms, investigating their algebraic properties. Finally, we explored negation and modal operators based on proposed radius conditions and examined their characteristics. This research contributes to a more explicit understanding of the properties and capabilities of CIFS, providing valuable insights into its potential applications, particularly in decision-making theory.
Citation: Dian Pratama, Binyamin Yusoff, Lazim Abdullah, Adem Kilicman, Nor Hanimah Kamis. Extension operators of circular intuitionistic fuzzy sets with triangular norms and conorms: Exploring a domain radius[J]. AIMS Mathematics, 2024, 9(5): 12259-12286. doi: 10.3934/math.2024599
The circular intuitionistic fuzzy set (CIFS) extends the concept of IFS, representing each set element with a circular area on the IFS interpretation triangle (IFIT). Each element in CIFS is characterized not only by membership and non-membership degrees but also by a radius, indicating the imprecise areas of these degrees. While some basic operations have been defined for CIFS, not all have been thoroughly explored and generalized. The radius domain has been extended from $ [0, 1] $ to $ [0, \sqrt{2}] $. However, the operations on the radius domain are limited to $ min $ and $ max $. We aimed to address these limitations and further explore the theory of CIFS, focusing on operations for membership and non-membership degrees as well as radius domains. First, we proposed new radius operations on CIFS with a domain $ [0, \psi] $, where $ \psi \in [1, \sqrt{2}] $, called a radius algebraic product (RAP) and radius algebraic sum (RAS). Second, we developed basic operators for generalized union and intersection operations on CIFS based on triangular norms and conorms, investigating their algebraic properties. Finally, we explored negation and modal operators based on proposed radius conditions and examined their characteristics. This research contributes to a more explicit understanding of the properties and capabilities of CIFS, providing valuable insights into its potential applications, particularly in decision-making theory.
[1] | L. A. Zadeh, Fuzzy Set, Inf. Control, 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X doi: 10.1016/S0019-9958(65)90241-X |
[2] | K. T. Atanassov, Intuitionistic Fuzzy Sets, Fuzzy Sets Syst., 20 (1986), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3 doi: 10.1016/S0165-0114(86)80034-3 |
[3] | B. Yusoff, A. Kilicman, D. Pratama, R. Hasni, Circular q-Rung Orthopair Fuzzy Set and Its Algebraic Properties, Malays. J. Math. Sci., 17 (2023), 363–378. https://doi.org/10.47836/mjms.17.3.08 doi: 10.47836/mjms.17.3.08 |
[4] | V. N. Dixit, R. Kumar, N. Ajmal, On Fuzzy Rings, Fuzzy Sets Syst., 49 (1992), 205–213. https://doi.org/10.1016/0165-0114(92)90325-X doi: 10.1016/0165-0114(92)90325-X |
[5] | M. Yamin, P. K. Sharma, Intuitionistic Fuzzy Rings with Operators, Int. J. Math. Comput. Sci., 6 (2018), 1860–1866. https://doi.org/10.18535/ijmcr/v6i2.01 doi: 10.18535/ijmcr/v6i2.01 |
[6] | D. Pratama, Operators $\boxplus$A and $\boxtimes$A on Intuitionistic Fuzzy Ring, JMP, 12 (2020), 35–46. https://doi.org/10.20884/1.jmp.2020.12.1.2613 doi: 10.20884/1.jmp.2020.12.1.2613 |
[7] | K. T. Atanassov, Review and New Result on Intuitionistic Fuzzy Sets, Int. J. Bioautomotion, 20 (2016), 17–26. |
[8] | P. A. Ejegwa, S. O. Akowe, P. M. Otene, J. M. Ikyule, An Overview on Intuitionistic Fuzzy Sets, Int. J. Sci. Technol. Res., 3 (2014), 142–145. |
[9] | A. S. Alkouri, A. R. Salleh, Complex Intuitionistic Fuzzy Sets, AIP Conf. Proc., 1482 (2021), 464–470. https://doi.org/10.1063/1.4757515 doi: 10.1063/1.4757515 |
[10] | B. Yusoff, I. Taib, L. Abdullah, A. F. Wahab, A New Similarity Measure on Intuitionistic Fuzzy Sets, Int. J. Math. Comput. Sci., 5 (2011), 819–823. https://doi.org/10.5281/zenodo.1054905 doi: 10.5281/zenodo.1054905 |
[11] | S. Ontanon, An Overview of Distance and Similarity Functions for Structured Data, Artif. Intell. Rev., 53 (2020), 5309–5351. https://doi.org/10.1007/s10462-020-09821-w doi: 10.1007/s10462-020-09821-w |
[12] | A. M. Kozae, M. Shokry, M. Omran, Intuitionistic Fuzzy Sets and Its Application in Corona Covid-19, Appl. Comput. Math., 9 (2020), 146–154. http://doi.org/10.11648/j.acm.20200905.11 doi: 10.11648/j.acm.20200905.11 |
[13] | H. Aggarwal, H. D. Arora, V. Kumar, A Decision-making Problem as an Applications of Intuitionistic Fuzzy Set, Int. J. Eng. Adv. Technol., 9 (2019), 5259–5261. http://doi.org/10.35940/ijeat.A1053.129219 doi: 10.35940/ijeat.A1053.129219 |
[14] | P. A. Ejegwa, A. J. Akubo, O. M. Joshua, Intuitionistic Fuzzy Set and Its Application in Career Determination Via Normalized Euclidean Distance Method, Eur. Sci. J., 10 (2014), 529–536. |
[15] | H. Zhang, Linguistic intuitionistic fuzzy sets and application in MAGDM, J. Appl. Math., 2014 (2014), 432092. https://doi.org/10.1155/2014/432092 doi: 10.1155/2014/432092 |
[16] | K. T. Atanassov, G. Gargov, Interval-Valued Intuitionistic Fuzzy Sets, Fuzzy Sets Syst., 31 (1989), 343–349. https://doi.org/10.1016/0165-0114(89)90205-4 doi: 10.1016/0165-0114(89)90205-4 |
[17] | A. K. Adak, M. Bhowmik, Interval Cut-Set of Interval-Valued Intuitionistic Fuzzy Sets, Afr. J. Math. Comput. Sci. Res., 4 (2011), 192–200. |
[18] | K. T. Atanassov, On The Most Extended Modal Operator of First Type Over Interval-Valued Intuitionistic Fuzzy Sets, Mathematics, 6 (2018), 123. https://doi.org/10.3390/math6070123 doi: 10.3390/math6070123 |
[19] | R. Verma, J. M. Merigó, A New Decision Making Method Using Interval-Valued Intuitionistic Fuzzy Cosine Similarity Measure Based on the Weighted Reduced Intuitionistic Fuzzy Sets, Informatica, 31 (2020), 399–433. https://doi.org/10.15388/20-infor405 doi: 10.15388/20-infor405 |
[20] | D. Joshi, R. Kumar, Improved Accuracy Function for Interval-Valued Intuitionistic Fuzzy Sets and Its Application to Multi–Attributes Group Decision Making, Cybern. Syst., 49 (2018), 64–76. https://doi.org/10.1080/01969722.2017.1412890 doi: 10.1080/01969722.2017.1412890 |
[21] | C. Kahraman, B. Oztaysi, S. C. Onar, Interval-Valued Intuitionistic Fuzzy Confidence Intervals, J. Intell. Syst., 28 (2019), 307–319. https://doi.org/10.1515/jisys-2017-0139 doi: 10.1515/jisys-2017-0139 |
[22] | S. K. Bharati, Transportation Problem with Interval-Valued Intuitionistic Fuzzy Sets: Impact of A New Ranking, Prog. Artif. Intell., 10 (2021), 129–145. https://doi.org/10.1007/s13748-020-00228-w doi: 10.1007/s13748-020-00228-w |
[23] | L. Abdullah, N. Zulkifli, H. Liao, E. Herrera-Viedma, A. Al-Barakati, An Interval-Valued Intuitionistic Fuzzy DEMATEL Method Combined with Choquet Integral for Sustainable Solid Waste Management, Eng. Appl. Artif. Intell., 82 (2019), 207–215. https://doi.org/10.1016/J.ENGAPPAI.2019.04.005 doi: 10.1016/J.ENGAPPAI.2019.04.005 |
[24] | K. T. Atanassov, Circular Intuitionistic Fuzzy Sets, J. Intell. Fuzzy Syst., 39 (2020), 5981–5986. https://doi.org/10.3233/JIFS-189072 doi: 10.3233/JIFS-189072 |
[25] | K. T. Atanassov, E. Marinov, Four Distances for Circular Intuitionistic Fuzzy Sets, Mathematics, 9 (2021), 1121. https://doi.org/10.3390/math9101121 doi: 10.3390/math9101121 |
[26] | E. Cakir, M. A. Tas, Z. Ulukan, A New Circular Intuitionistic Fuzzy MCDM: A Case of Covid-19 Medical Waste Landfill Site Evaluation, 2021 IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI), 2021,143–148. https://doi.org/10.1109/CINTI53070.2021.9668563 |
[27] | C. Kahraman, N. Alkan, Circular Intuitionistic Fuzzy TOPSIS Method with Vague Membership Functions: Supplier Selection Application Context, Notes Intuitionistic Fuzzy Sets, 27 (2021), 24–52. https://doi.org/10.7546/nifs.2021.27.1.24-52 doi: 10.7546/nifs.2021.27.1.24-52 |
[28] | G. Imanov, A. Aliyev, Circular Intuitionistic Fuzzy Sets In Evaluation Of Human Capital, Rev. Cient. Del., 1 (2021), 1–13. |
[29] | M. Navara, Triangular Norms and Measures of Fuzzy Sets, In: Logical, Algebraic, Analytic and Probabilistic Aspects of Triangular Norms, Amsterdam : Elsevier B.V., 2005,345–390. https://doi.org/10.1016/B978-044451814-9/50013-6 |
[30] | E. P. Klement, R. Mesiar, E. G. Pap, Triangular Norms. Position paper Ⅰ : Basic Analytical and Algebraic Properties, Fuzzy Sets Syst., 143 (2004), 5–26. https://doi.org/10.1016/j.fss.2003.06.007 doi: 10.1016/j.fss.2003.06.007 |
[31] | G. Deschrijver, E. Kerre, A Generalization of Operators on Intuitionistic Fuzzy Sets Using Triangular Norms and Conorms, Notes Intuitionistic Fuzzy Sets, 8 (2002), 19–27. |
[32] | E. Boltürk, C. Kahraman, Interval-Valued and Circular Intuitionistic Fuzzy Present Worth Analyses, Informatica, 33 (2022), 693–711. https://doi.org/10.15388/22-infor478 doi: 10.15388/22-infor478 |
[33] | T. Y. Chen, Evolved distance measures for circular intuitionistic fuzzy sets and their exploitation in the technique for order preference by similarity to ideal solutions, Artif. Intell. Rev., 56 (2023), 7347–7401. https://doi.org/10.1007/s10462-022-10318-x doi: 10.1007/s10462-022-10318-x |
[34] | N. Alkan, C. Kahraman, Circular Intuitionistic Fuzzy TOPSIS Method: Pandemic Hospital Location Selection, J. Intell. Fuzzy Syst., 42 (2022), 295–316. https://doi.org/10.3233/JIFS-219193 doi: 10.3233/JIFS-219193 |
[35] | M. J. Khan, W. Kumam, N. A. Alreshidi, Divergence Measures for Circular Intuitionistic Fuzzy Sets and Their Applications, Eng. Appl. Artif. Intell., 116 (2022), 105455. https://doi.org/10.1016/j.engappai.2022.105455 doi: 10.1016/j.engappai.2022.105455 |
[36] | C. Kahraman, I. Otay, Extension of VIKOR Method Using Circular Intuitionistic Fuzzy Sets, In: Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation, Cham: Springer, 2021, 48–57. https://doi.org/10.1007/978-3-030-85577-2_6 |
[37] | I. Otay, C. Kahraman, A novel circular intuitionistic fuzzy AHP and VIKOR methodology: An application to a multi-expert supplier evaluation problem, Pamukkale Univ. J. Eng. Sci., 28 (2021), 194–207. |
[38] | D. Pratama, B. Yusoff, L. Abdullah, A. Kilicman, The generalized circular intuitionistic fuzzy set and its operations, AIMS Mathematics, 8 (2023), 26758–26781. http://doi.org/10.3934/math.20231370 doi: 10.3934/math.20231370 |
[39] | C. Xu, Y. Wen, New measure of circular intuitionistic fuzzy sets and its application in decision making, AIMS Mathematics, 8 (2023), 24053–24074. https://doi.org/10.3934/math.20231226 doi: 10.3934/math.20231226 |
[40] | B. Yusoff, D. Pratama, A. Kilicman, L. Abdullah, Circular Intuitionistic Fuzzy ELECTRE Ⅲ Model for Group Decision Analysis, Informatica, 34 (2023), 881–908. https://doi.org/10.15388/23-INFOR536 doi: 10.15388/23-INFOR536 |
[41] | N. A. Alreshidi, Z. Shah, M. J. Khan, Similarity and Entropy Measures for Circular Intuitionistic Fuzzy Sets, Eng. Appl. Artif. Intell., 131 (2024), 107786. https://doi.org/10.1016/j.engappai.2023.107786 doi: 10.1016/j.engappai.2023.107786 |
[42] | M. Bozyigit, M. Olgun, M. Unver, Circular Pythagorean Fuzzy Sets and Applications to Multi-Criteria Decision Making, Informatica, 34 (2023), 713–742. https://doi.org/10.15388/23-INFOR529 doi: 10.15388/23-INFOR529 |
[43] | S. Ashraf, M. S. Chohan, S. Muhammad, F. Khan, Circular Intuitionistic Fuzzy TODIM Approach for Material Selection for Cryogenic Storage Tank for Liquid Nitrogen Transportation, IEEE Access, 11 (2023), 98458–98468. https://doi.org/10.1109/ACCESS.2023.3312568 doi: 10.1109/ACCESS.2023.3312568 |
[44] | H. Garg, M. Unver, M. Olgun, E. Turkarslan, An Extended EDAS Method with Circular Intuitionistic Fuzzy Value Features and Its Application to Multi-Criteria Decision-Making Process, Artif. Intell. Rev., 56 (2023), 3173–3204. https://doi.org/10.1007/s10462-023-10601-5 doi: 10.1007/s10462-023-10601-5 |
[45] | E. Cakir, E. Demircioglu, Circular intuitionistic Fuzzy PROMETHEE Methodology: A Case of Smart Cities Evaluation, In: Intelligent and Fuzzy Systems, Cham: Springer, 2023,353–361. https://doi.org/10.1007/978-3-031-39777-6_43 |
[46] | M. Alimohammadlou, S. Alinejad, Z. Khoshsepehr, M. Safari, Y. Jafari, A. Tajodin, et al., Circular Intuitionistic Fuzzy AHP: An Application in Manufacturing Sector, In: Analytic Hierarchy Process with Fuzzy Sets Extensions, Cham: Springer, 2023,369–394. https://doi.org/10.1007/978-3-031-39438-6_17 |