Extensions of prioritized weighted aggregation operators for decision-making under complex q-rung orthopair fuzzy information

Prioritized Aggregation Operators for Intuitionistic Fuzzy Information Based on Aczel–Alsina T-Norm and T-Conorm and Their Applications in Group Decision-Making

In multi-attribute group decision-making (MAGDM) problems, prioritization is sometimes important. Several techniques and methods have been introduced in fuzzy systems to use prioritization. The main purpose of this paper is to propose prioritized aggregation operators (AOs) for intuitionistic fuzzy (IF) information. These AOs are symmetric in nature and are based on the novel Aczel–Alsina t-norm and t-conorm. Herein, we propose IF-prioritized Aczel–Alsina averaging (IFPAAA) and IF-prioritized Aczel–Alsina geometric (IFPAAG) operators. It is shown that these AOs satisfy the basic features of aggregation. Some additional results for these AOs are also investigated. These proposed operators can capture the prioritization phenomenon among the aggregated arguments, and the weights for prioritization are obtained from expert information. Finally, the proposed AOs are used in an MAGDM problem where a doctor is selected for a hospital. A comparison of the proposed prioritized AOs is also established with other well-known AOs to show the significance of the IFPAAA and IFPAAG operators.

Yager aggregation operators based on complex interval-valued q-rung orthopair fuzzy information and their application in decision making

As a more massive feasible and prominent tool than the complex interval-valued Pythagorean fuzzy (CIVPF) set and complex interval-valued intuitionistic fuzzy (CIVIF) set, the complex interval-valued q-rung orthopair fuzzy (CIVQROF) set has been usually used to represent ambiguity and vagueness for real-life decision-making problems. In this paper, we firstly proposed some distance measures, Yager operational laws, and their comparison method. Further, we developed CIVQROF Yager weighted averaging (CIVQROFYWA), CIVQROF Yager ordered weighted averaging (CIVQROFYOWA), CIVQROF Yager weighted geometric (CIVQROFYWG), CIVQROF Yager ordered weighted geometric (CIVQROFYOWG) operators with CIVQROF information, and some certain well-known and feasible properties and outstanding results are explored in detail. Moreover, we proposed a new and valuable technique for handling multi-attribute decision-making problems with CIVQROF information. Lastly, a practical evaluation regarding the high blood pressure diseases of the patient is evaluated to illustrate the feasibility and worth of the proposed approaches.

Complex Interval-Valued q-Rung Orthopair Fuzzy Hamy Mean Operators and Their Application in Decision-Making Strategy

This paper deals with uncertainty, asymmetric information, and risk modelling in a complex power system. The uncertainty is managed by using probability and decision theory methods. Multi-attribute decision-making (MADM) technique is a very effective and well-known tool to investigate fuzzy information more effectively. However, the selection of houses cannot be carried out by utilizing symmetry information, because enterprises does not have complete information, so asymmetric information should be used when selecting enterprises. Hamy mean (HM) operator is a feasible tool to handle strategic decision-making problems because it can capture the order between the finite input terms. Additionally, the complex interval-valued q-rung orthopair fuzzy (CIVq-ROF) setting is a broadly flexible and massively dominant technique to operate problematic and awkward data in actual life problems. The major contribution of this analysis is how to aggregate the collection of alternatives into a singleton set, for this we analyzed the technique of CIVq-ROF Hamy mean (CIVq-ROFHM) operator and CIVq-ROF weighted Hamy mean (Cq-ROFWHM) operator and some well-known results are deliberated. Keeping the advantages of the parameters in HM operators, we discussed the specific cases of the invented operators. To investigate the decision-making problems based on CIVq-ROF information, we suggested the following multi-attribute decision-making (MADM) technique to determine the beneficial term from the finite group of alternatives with the help of evaluating several examples. This manuscript showed how to make decisions when there is asymmetric information about enterprises. Finally, based on the evaluating examples, we try to discover the sensitive analysis and supremacy of the invented operators to find the flexibility and dominancy of the diagnosed approaches.

Analysis of medical diagnosis based on variation co-efficient similarity measures under picture hesitant fuzzy sets and their application

One of the most dominant and feasible technique is called the PHF setting is exist in the circumstances of fuzzy set theory for handling intricate and vague data in genuine life scenario. The perception of PHF setting is massive universal is compared to these assumptions, who must cope with two or three sorts of data in the shape of singleton element. Under the consideration of the PHF setting, we utilized some SM in the region of the PHF setting are to diagnose the PHFDSM, PHFWDSM, PHFJSM, PHFWJSM, PHFCSM, PHFWCSM, PHFHVSM, PHFWHVSM and demonstrated their flexible parts. Likewise, a lot of examples are exposed under the invented measures based on PHF data in the environment of medical diagnosis to demonstrate the stability and elasticity of the explored works. Finally, the sensitive analysis of the presented works is also implemented and illuminated their graphical structures.

Multi-criteria decision-making algorithm based on aggregation operators under the complex interval-valued q-rung orthopair uncertain linguistic information

The paper aims to present a concept of a Complex interval-valued q-rung orthopair uncertain linguistic set (CIVQROULS) and investigated their properties. In the presented set, the membership grades are considered in terms of the interval numbers under the complex domain while the linguistic features are added to address the uncertainties in the data. To further discuss more, we have presented the operation laws and score function for CIVQROULS. In addition to them, we present some averaging and geometric operators to aggregate the different pairs of the CIVQROULS. Some fundamental properties of the proposed operators are stated. Afterward, an algorithm for solving the decision-making problems is addressed based on the proposed operator using the CIVQROULS features. The applicability of the algorithm is demonstrated through a case study related to brain tumors and their effectiveness is compared with the existing studies.

A mathematical approach to medical diagnosis via Pythagorean fuzzy soft TOPSIS, VIKOR and generalized aggregation operators

Hepatitis is a therapeutic disorder caused by the inflammation/infection of liver and regarded as the existence of cells causing inflammation in the tissues of body parts. Hepatitis is deliberated as a lethal disease worldwide, especially in developing countries mainly due to contaminated drinking water, unhygienic sanitary conditions and careless blood transfusion. This infection is basically considered as viral infection even though this sort of liver infection can also take place due to autoimmune, toxin, medications, unprotected physical relations, drugs and alcohol. Many approaches of identifying viral hepatitis have been sought so for, which include physical inspection, liver function tests (LFTs), liver surgery (biopsy), imaging studies such as sonogram or CT scan, ultrasound, blood tests, viral serology panel, DNA test, and viral antibody testing. In this article, we propose mathematical analysis of viral hepatitis types using Pythagorean fuzzy soft sets (PFSSs) via TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), VIKOR (Vise Kriterijumska Optimizacija Kompromisno Resenje) and generalized aggregation operators models and show that all the three techniques render the same optimal choice. We also present a commentary yielding comparison between the three techniques considering their structure of evaluation.

A hybrid decision making method based on q-rung orthopair fuzzy soft information

Soft set (SfS) theory is a basic tool to handle vague information with parameterized study during the process as compared to fuzzy as well as q-rung orthopair fuzzy theory. This research article is devoted to establish some general aggregation operators (AOs), based on Yager’s norm operations, to cumulate the q-rung orthopair fuzzy soft data in decision making environments. In this article, the valuable properties of q-rung orthopair fuzzy soft set (q - ROFSfS) are merged with the Yager operator to propose four new operators, namely, q-rung orthopair fuzzy soft Yager weighted average (q - ROFSfYWA), q-rung orthopair fuzzy soft Yager ordered weighted average (q - ROFSfYOWA), q-rung orthopair fuzzy soft Yager weighted geometric (q - ROFSfYWG) and q-rung orthopair fuzzy soft Yager ordered weighted geometric (q - ROFSfYOWG) operators. The dominant properties of proposed operators are elaborated. To emphasize the importance of proposed operators, a multi-attribute group decision making (MAGDM) strategy is presented along with an application in medical diagnosis. The comparative study shows superiorities of the proposed operators and limitations of the existing operators. The comparison with Pythagorean fuzzy TOPSIS (PF-TOSIS) method shows that PF-TOPSIS method cannot deal with data involving parametric study but developed operators have the ability to deal with decision making problems using parameterized information.

Extensions of power aggregation operators for decision making based on complex picture fuzzy knowledge

This article puts forward an innovative notion of complex picture fuzzy set (CPFS) which is particularly an extension and a generalization of picture fuzzy sets (PFSs) by the addition of phase term in the description of PFSs. The uniqueness of CPFS lies in the capability to manage the uncertainty and periodicity, simultaneously, due to the presence of phase term which broadens the range of CPFS from a real plane to the complex plane of unit disk. We describe and verify the fundamental operations and properties of CPFSs. We introduce the aggregation operators, namely; complex picture fuzzy power averaging and complex picture fuzzy power geometric operators in CPFSs environment, based on weighted and ordered weighted averaging and geometric operators. We construct multi-criteria decision making (MCDM) problem, using these operators and describe a numerical example to illustrate the validity and competence of this article. Finally, we discuss the advantages of this generalized concept of aggregation technique and analyze a comparative study to demonstrate the superiority and consistency of our model.

Group decision-making for the selection of an antivirus mask under fermatean fuzzy soft information

With the rapid increase of COVID-19, mostly people are facing antivirus mask shortages. It is necessary to select a good antivirus mask and make it useful for everyone. For maximize the efficacy of the antivirus masks, we propose a decision support algorithm based on the concept of Fermatean fuzzy soft set (FFSfS). The basic purpose of this article is to introduce the notion of FFSfS to deal with problems involving uncertainty and complexity corresponding to various parameters. Here, the valuable properties of FFSfS are merged with the Yager operator to propose four new operators, namely, Fermatean fuzzy soft Yager weighted average (FFSfYWA), Fermatean fuzzy soft Yager ordered weighted average (FFSfYOWA), Fermatean fuzzy soft Yager weighted geometric (FFSfYWG) and Fermatean fuzzy soft Yager ordered weighted geometric (FFSfYOWG) operators. The fundamental properties of proposed operators are discussed. For the importance of proposed operators, a multi-attribute group decision-making (MAGDM) strategy is presented along with an application for the selection of an antivirus mask over the COVID-19 pandemic. The comparison with existing operators shows that existing operators cannot deal with data involving parametric study but developed operators have the ability to deal decision-making problems using parameterized information.

Geometric-arithmetic energy and atom bond connectivity energy of dual hesitant q-rung orthopair fuzzy graphs

 q-Rung orthopair fuzzy sets (q-ROFSs), originally proposed by Yager, can powerfully modify the range of indication of decision information by changing a parameter q based on the different hesitation degree, and the dual hesitant q-rung orthopair fuzzy set (DHq-ROFS), a new technique to consider human’s hesitance, can be more substantial of dealing with real multi-attribute decision making (MADM) problems. Inspired by DHq-ROFSs, in this article, we extend the concept of q-rung orthopair fuzzy graphs to dual hesitant q-rung orthopair fuzzy context and introduce the innovative concept of a dual hesitant q-rung orthopair fuzzy graphs based on Hamacher operator called dual hesitant q-rung orthopair fuzzy Hamacher graphs (DHq-ROFHGs). We propose the new concepts of geometric-arithmetic energy and atom bond connectivity energy of a DHq-ROFHG and determine its upper and lower bounds. Moreover, on the basis of the proposed concept of DHq-ROFHGs, we introduce a new approach to solve the MADM problems with dual hesitant q-rung orthopair fuzzy information. At the end, we give a numerical model related to the selection of most significant defensive factor to illustrate the applicability of the developed approach, and exhibit its viability. Comparative analysis is conducted and the superiorities are illustrated.