Complex T-Spherical Fuzzy Relations With Their Applications in Economic Relationships and International Trades

Uncertainty is the unavoidable part of the life. In almost all circumstances, we regularly find ourselves in a state of uncertainty. Several reasons can lead to uncertainty, such as randomness, vagueness and rough knowledge. Fuzzy set (FS) theory deals with these kinds of information. Many generalizations had been made in the theory of FSs, such as intuitionistic FSs (IFSs), q-rung orthopair FSs (qROFSs), complex qROFSs (CqROFSs), spherical FSs (SFSs), T-spherical FSs (TSFSs), and complex TSFSs (CTSFSs). Among these generalizations of FSs, the CTSFSs are the most dominant generalization of the FSs. Although fuzzy relations (FRs), IF relations (IFRs) and complex FRs (CFRs) were defined in the literature, the concepts of relations have not yet been introduced in the CTSFSs. This paper unveils the novel concept of CTSF relations (CTSFRs), which provides the extensive generalizations of FRs. The proposed CTSFRs can give many generalized types of FRs, such as IFRs, CFRs, Pythagorean FRs, qROFRs, SFRs and TSFRs, etc. Additionally, some useful properties and results are obtained for CTSFRs. Moreover, a couple of applications demonstrate the usefulness of the proposed concepts. These CTSFRs can be used to depict the time-related interdependence of global market. Thus, we apply these CTSFRs to analyze the interdependence of the international trades among countries and compare the financial factors affecting business markets. Furthermore, the economic relationships with respect to time lag can be modeled by using the CTSFSs and the CTSFRs. Finally, a comparative analysis illuminates the supremacy of the proposed way in contrast with the existing ones.

[1]  Zeshui Xu,et al.  Integrations of q-Rung Orthopair Fuzzy Continuous Information , 2019, IEEE Transactions on Fuzzy Systems.

[2]  Fuyuan Xiao,et al.  Generalization of Dempster–Shafer theory: A complex mass function , 2020, Applied Intelligence.

[3]  Theresa Beaubouef,et al.  Rough Sets , 2019, Lecture Notes in Computer Science.

[4]  Ronald R. Yager,et al.  Generalized Orthopair Fuzzy Sets , 2017, IEEE Transactions on Fuzzy Systems.

[5]  Harish Garg,et al.  Exponential operation and aggregation operator for q‐rung orthopair fuzzy set and their decision‐making method with a new score function , 2018, Int. J. Intell. Syst..

[6]  Harish Garg,et al.  Linguistic Pythagorean fuzzy sets and its applications in multiattribute decision‐making process , 2018, Int. J. Intell. Syst..

[7]  Shahzad Faizi,et al.  Intuitionistic Fuzzy Sets in Multi-Criteria Group Decision Making Problems Using the Characteristic Objects Method , 2020, Symmetry.

[8]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[9]  Tahir Mahmood,et al.  On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition , 2019, Complex & Intelligent Systems.

[10]  Bui Cong Cuong,et al.  Picture fuzzy sets , 2015 .

[11]  Harish Garg,et al.  Some results on information measures for complex intuitionistic fuzzy sets , 2019, Int. J. Intell. Syst..

[12]  Tahir Mahmood,et al.  Similarity Measures for T-Spherical Fuzzy Sets with Applications in Pattern Recognition , 2018, Symmetry.

[13]  Nasreen Kausar,et al.  A Novel Applications of Complex Intuitionistic Fuzzy Sets in Group Theory , 2020, IEEE Access.

[14]  Harish Garg,et al.  Algorithm for T-Spherical Fuzzy Multi-Attribute Decision Making Based on Improved Interactive Aggregation Operators , 2018, Symmetry.

[15]  Miin-Shen Yang,et al.  Fuzzy Entropy for Pythagorean Fuzzy Sets with Application to Multicriterion Decision Making , 2018, Complex..

[16]  Zahid Hussain,et al.  Belief and Plausibility Measures on Intuitionistic Fuzzy Sets with Construction of Belief-Plausibility TOPSIS , 2020, Complex..

[17]  J. Mendel Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[18]  Qaisar Khan,et al.  An approach toward decision-making and medical diagnosis problems using the concept of spherical fuzzy sets , 2019, Neural Computing and Applications.

[19]  Humberto Bustince Sola,et al.  Intuitionistic fuzzy relations (Part I) , 1995 .

[20]  Abraham Kandel,et al.  On complex fuzzy sets , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[21]  Bo Hu,et al.  Distances of complex fuzzy sets and continuity of complex fuzzy operations , 2018, J. Intell. Fuzzy Syst..

[22]  Ganeshsree Selvachandran,et al.  The algebraic structures of complex intuitionistic fuzzy soft sets associated with groups and subgroups , 2018 .

[23]  Fuyuan Xiao,et al.  CED: A Distance for Complex Mass Functions , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[24]  Yousef Al-Qudah,et al.  Complex Multi-Fuzzy Soft Set: Its Entropy and Similarity Measure , 2018, IEEE Access.

[25]  Harish Garg,et al.  Correlation coefficients for T-spherical fuzzy sets and their applications in clustering and multi-attribute decision making , 2020, Soft Comput..

[26]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[27]  Shyi-Ming Chen,et al.  Multiple-Attribute Group Decision-Making Based on q-Rung Orthopair Fuzzy Power Maclaurin Symmetric Mean Operators , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[28]  Faruk Karaaslan,et al.  A new approach to bipolar soft sets and its applications , 2014, Discret. Math. Algorithms Appl..

[29]  Peide Liu,et al.  Complex q-Rung Orthopair Fuzzy Aggregation Operators and Their Applications in Multi-Attribute Group Decision Making , 2019, Inf..

[30]  Tahir Mahmood,et al.  Evaluation of Investment Policy Based on Multi-Attribute Decision-Making Using Interval Valued T-Spherical Fuzzy Aggregation Operators , 2019, Symmetry.

[31]  D. Molodtsov Soft set theory—First results , 1999 .

[32]  Jian-Ping Fan,et al.  Divergence Measure of T-Spherical Fuzzy Sets and its Applications in Pattern Recognition , 2020, IEEE Access.

[33]  Hui Gao,et al.  Some q‐rung orthopair fuzzy Heronian mean operators in multiple attribute decision making , 2018, Int. J. Intell. Syst..

[34]  Zeeshan Ali,et al.  Complex T-Spherical Fuzzy Aggregation Operators with Application to Multi-Attribute Decision Making , 2020, Symmetry.

[35]  Zahid Hussian,et al.  Distance and similarity measures of Pythagorean fuzzy sets based on the Hausdorff metric with application to fuzzy TOPSIS , 2019, Int. J. Intell. Syst..

[36]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[37]  T. Mahmood A Novel Approach towards Bipolar Soft Sets and Their Applications , 2020, Journal of Mathematics.

[38]  Tahir Mahmood,et al.  Spherical fuzzy sets and their applications in multi-attribute decision making problems , 2019, J. Intell. Fuzzy Syst..

[39]  Cengiz Kahraman,et al.  Extension of WASPAS with Spherical Fuzzy Sets , 2019, Informatica.

[40]  Ronald R. Yager,et al.  Pythagorean fuzzy subsets , 2013, 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS).

[41]  Zichang Huang,et al.  Complex Cubic Fuzzy Aggregation Operators With Applications in Group Decision-Making , 2020, IEEE Access.

[42]  Fuyuan Xiao CEQD: A Complex Mass Function to Predict Interference Effects , 2021, IEEE Transactions on Cybernetics.

[43]  Shouzhen Zeng,et al.  A multi‐criteria sustainable supplier selection framework based on neutrosophic fuzzy data and entropy weighting , 2020 .

[44]  Muhammad Shabir,et al.  On fuzzy bipolar soft sets, their algebraic structures and applications , 2014, J. Intell. Fuzzy Syst..

[45]  Yong Deng,et al.  A New Divergence Measure of Pythagorean Fuzzy Sets Based on Belief Function and Its Application in Medical Diagnosis , 2020, Mathematics.

[46]  Cengiz Kahraman,et al.  Spherical fuzzy sets and spherical fuzzy TOPSIS method , 2019, J. Intell. Fuzzy Syst..

[47]  Cengiz Kahraman,et al.  A novel spherical fuzzy analytic hierarchy process and its renewable energy application , 2020, Soft Comput..

[48]  Runtong Zhang,et al.  Some Partitioned Maclaurin Symmetric Mean Based on q-Rung Orthopair Fuzzy Information for Dealing with Multi-Attribute Group Decision Making , 2018, Symmetry.

[49]  Abdul Razak Salleh,et al.  Complex intuitionistic fuzzy sets , 2012 .

[50]  Abraham Kandel,et al.  Complex fuzzy logic , 2003, IEEE Trans. Fuzzy Syst..

[51]  Wen Sheng Du,et al.  Minkowski‐type distance measures for generalized orthopair fuzzy sets , 2018, Int. J. Intell. Syst..