Organizations need to choose an appropriate systems security engineering approach to enable them to design and create systems that are secure and resistant to threats in areas where the impacts of security threats are severe. However, this decision-making process may inherently contain bipolarity and vagueness because the criteria used to evaluate systems security engineering approaches may have positive and negative aspects (characteristics). Overlooking these bipolar aspects may result in inadequate or skewed assessments of the risks, which in turn will hamper the ability to address them appropriately. In response to this challenge, this research develops a new methodological framework that combines bipolar fuzzy set theory and generalized power aggregation operators into multi-criteria decision-making for choosing systems security engineering approaches. This new mathematical framework would be known as the bipolar fuzzy multi-criteria decision-making technique and is applicable to solve all sorts of multi-criteria decision-making dilemmas, where bipolarity is involved such as selection of systems security engineering, selection of artificial intelligence models, etc. Thus, further, this manuscript analyzes and solves a case study of the identification and selection of the finest systems security engineering approach through a bipolar fuzzy multi-criteria decision-making technique. To reveal the benefits and supremacy of the initiated technique over the existing ones, this manuscript contains a comparative analysis.

Complex q-rung orthopair fuzzy sets (CQROFSs) are proposed to convey vague material in decision-making problems. The CQROFSs can enthusiastically modify the region of proof by altering the factor q ≥ 1 for real and imaginary parts based on the variation degree and, therefore, favor further uncountable options. Consequently, this set reverses over the existing theories, such as complex intuitionistic fuzzy sets (CIFSs) and complex Pythagorean fuzzy sets (CPFS). In everyday life, there are repeated situations that can occur, which involve an impartial assertiveness of the decision-makers. To determine the best decision to handle such situations, in this study, we propose modern operational laws by joining the characteristics of the truth factor sum and collaboration between the truth degrees into the analysis for CQROFSs. Based on these principles, we determined several weighted averaging neutral aggregation operators (AOs) to collect the CQROF knowledge. Subsequently, we established an original multiattribute decision-making (MADM) procedure by using the demonstrated AOs based on CQROFS. To evaluate the effectiveness, in terms of reliability and consistency, of the proposed operators, they were applied to some numerical examples. A comparative analysis of the investigated operators and other existing operators was also performed to find the dominance and validity of the introduced MADM method.

The notions of the bipolar complex fuzzy set (BCFS) and complex bipolar fuzzy set (CBFS) have been already given, but these notions of BCFS and CBFS have the problem that they contradict the basic definition of the complex numbers which we discussed in this article, and then we defined the new definition of BCFS. Our defined notion of BCFS is more closed to bipolarity as compared with already existing BCFS and CBFS, and more accurate. BCFS is the fusion of bipolar fuzzy set (BFS) which a decision analyst needs to describe the positive and negative aspects of an object and complex fuzzy set (CFS) which a decision analyst needs to handle two-dimensional (two variables) information. When there is information of two variables with positive and negative aspects then a decision analyst needs BCFS to handle this information. In this article, we also interpreted some basic operations on BCFS like a complement, intersection, and union and explained them with the help of examples. Additionally, we defined the concept of type-1 partially BCFS and type-2 partially BCFS. Further, we interpreted some generalized trigonometric similarity measures such as generalized cosine similarity measure, generalized tangent similarity measure, generalized cotangent similarity measure, and generalized hybrid trigonometric similarity measure for BCFS. The weighted generalized trigonometric similarity measures are also presented in this article. After that, we applied these similarity measures (SMs) in two real-life applications (pattern recognition and medical diagnosis) to show the benefits and advantages of our proposed SMs. Finally, we did a comparison of our demonstrated SMs with some existing SMs to show the superiority, usefulness, and effectiveness of our proposed SMs.

Abstract The interval‐valued q‐rung orthopair fuzzy set (IVq‐ROFS) and complex fuzzy set (CFS) are two generalizations of the fuzzy set (FS) to cope with uncertain information in real decision making problems. The aim of the present work is to develop the concept of complex interval‐valued q‐rung orthopair fuzzy set (CIVq‐ROFS) as a generalization of interval‐valued complex fuzzy set (IVCFS) and q‐rung orthopair fuzzy set (q‐ROFS), which can better express the time‐periodic problems and two‐dimensional information in a single set. In this article not only basic properties of CIVq‐ROFSs are discussed but also averaging aggregation operator (AAO) and geometric aggregation operator (GAO) with some desirable properties and operations on CIVq‐ROFSs are discussed. The proposed operations are the extension of the operations of IVq‐ROFS, q‐ROFS, interval‐valued Pythagorean fuzzy, Pythagorean fuzzy (PF), interval‐valued intuitionistic fuzzy, intuitionistic fuzzy, complex q‐ROFS, complex PF, and complex intuitionistic fuzzy theories. Further, the Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) method are also examine based on CIVq‐ROFS to explore the reliability and proficiency of the work. Moreover, we discussed the advantages of CIVq‐ROFS and showed that the concepts of IVCFS and q‐ROFS are the special cases of CIVq‐ROFS. Moreover, the flexibility of proposed averaging aggregation operator and geometric aggregation operator in a multi‐attribute decision making (MADM) problem are also discussed. Finally, a comparative study of CIVq‐ROFSs with pre‐existing work is discussed in detail.

In this manuscript, the technique of the generalized MULTIMOORA method is investigated by using the concept of a T-spherical fuzzy set (T-SFS), which is the modified idea of a picture fuzzy set to handle awkward and vague information in daily life problems. T-SFS covers the degree of truth, abstinence, and falsity with a rule that the sum of the qth-powers of all degrees is restricted to the unit interval. Moreover, for examining the interrelationships among any number of T-SFSs, we construct the idea of T-spherical fuzzy Dombi prioritized weighted arithmetic (T-SFDPWA) aggregation operators, T-spherical fuzzy Dombi prioritized arithmetic, T-spherical fuzzy Dombi prioritized geometric, and T-spherical fuzzy Dombi prioritized weighted geometric (T-SFDPWG) aggregation operators are given. Then, the basic properties of T-SFDPWA and T-SFDPWG aggregation operators are investigated and discussed in some of their cases. The investigated operators based on T-SFS are utilized in the environment of multiattribute decision-making problems to find the consistency and proficiency of the developed operators. In last, we illustrated some numerical examples based on explored operators is to examine the reliability and validity of the investigated operators with the help of comparative analysis and graphical representations with some existing ideas to show the presented approaches are extensive powerful.

To cope with awkward and unreliable information in daily life issues, the theory of interval-valued picture fuzzy set (IVPFS) is a useful idea to manage unpredictable and vague information. An IVPFS contains the degree of truth, abstinence, and falsity in the finite subset of a unit interval with a rule that is the sum of the upper parts of all degrees is cannot exceed from unit interval. In this study, to find the interrelationships among any number of IVPFSs, we examined the interval-valued picture fuzzy frank averaging operator, interval-valued picture fuzzy frank weighted averaging operator, interval-valued picture fuzzy frank weighted geometric operator and discussed their properties. Moreover, some special cases of the presented operators based on IVPFSs are also discovered. The analytic hierarchy process (AHP) by using the IVPFSs is also explored and discussed in their different aspects. Finally, a multiattribute decision-making procedure is investigated by using proposed operators based on IVPFSs. We illustrated some numerical examples based on explored frank aggregation operators and AHP methods to examine the feasibility and validity of the presented approaches. The comparative analysis, geometrical representations, advantages of the investigated approaches are also discussed.

Molodtsov investigated the pioneer notion of soft set (SfS) which provides a general framework for mathematical problems by affix parameterization tools during the analysis as compared to fuzzy set and q-rung orthopair fuzzy set (q-ROFS). The aim of this manuscript is to investigate the notion of q-rung orthopair fuzzy soft set (q-ROFSfS), which provide a lay of foundation for those difficulties and complexities which the contemporary theories face during the study of uncertainty. Therefore, our main contribution in this manuscript is to investigate the q-rung orthopair fuzzy soft weighted averaging, q-rung orthopair fuzzy soft ordered weighted averaging and q-rung orthopair fuzzy soft hybrid averaging operators in q-ROF soft (q-ROFSf) environment. Further, the fundamental properties of these aggregation operators are studied. On the base of developed approach an algorithm for multicriteria decision making method is being presented. An application of medical diagnosis problems is solved on the proposed algorithm under the q-ROFSf environment. Finally, comparison between the developed operators with some existing operators are being presented showing the superiority and efficiency of the developed approach than the existing literature.

Many different types of ranking methods based on the score and accuracy functions of intuitionistic fuzzy values (IFVs) exist in the literature. The notion of knowledge bases, as in the case of rough set theory, is very handy to show that every ranking technique produces a unique classification of IFVs with a unique order among the classes. This means these rankings give rise to unique knowledge bases. Therefore, ranking of IFVs by two or more distinct techniques may produce different results. In this study, a graphical ranking method based on the uncertainty index and entropy is proposed. This approach is tested on several numerical examples existing in the literature and shown to be intuitive and convenient for applications in real-life scenarios.

A pythagorean fuzzy set is a generalized fuzzy structure that copes with imprecisions of real life accurately and with a larger domain. The aim of this manuscript is to develop the notion of graph for newly established concept of interval-valued Pythagorean fuzzy set. We introduced the concept of interval-valued Pythagorean fuzzy graph (IVPyFG) and discussed its related ideas with the help of examples. The significance of using interval-valued fuzzy concepts over non-interval-valued fuzzy concepts are demonstrated numerically. Further, the advantages of using the new approach over the pre-existing ideas are demonstrated with the help of numerical examples. The main goal of this article is to study three types of decision-making problems using the framework of IVPyFGs. These three problems include the problem of selection of the best university in a network of universities, a supply chain management problem and the shortest path problem. The comparison of the new approach toward these problems with existing approaches is also established.