Aggregation Operators Research Articles

A Systematic Analysis of EDAS Method and Power Aggregation Operators Based on Bipolar Complex Fuzzy Linguistic for Rural Energy Infrastructure Decision

A Systematic Analysis of EDAS Method and Power Aggregation Operators Based on Bipolar Complex Fuzzy Linguistic for Rural Energy Infrastructure Decision

Evaluation of Data Analysis Software Using T-Spherical Fuzzy Einstein Aggregation Operators With Unknown Weights

Evaluation of Data Analysis Software Using T-Spherical Fuzzy Einstein Aggregation Operators With Unknown Weights

Impact of AI Techniques in Electrical Engineering With Spherical Fuzzy Soft Geometric Aggregation Operators

Impact of AI Techniques in Electrical Engineering With Spherical Fuzzy Soft Geometric Aggregation Operators

Selection of Software Development Methodology by Employing a Multi-Criteria Decision-Making Approach Based on Logarithmic Bipolar Complex Fuzzy Aggregation Operators

Selection of Software Development Methodology by Employing a Multi-Criteria Decision-Making Approach Based on Logarithmic Bipolar Complex Fuzzy Aggregation Operators

Q-Spherical Fuzzy Rough Einstein Geometric Aggregation Operator for Image Understanding and Interpretations

q-Spherical Fuzzy Rough Einstein Geometric Aggregation Operator for Image Understanding and Interpretations

New type of Diophantine neutrosophic aggregation operators and its extension

We introduce the concept of new type of Diophantine neutrosophic set. A Diophatine neutrosophic set is the new type of a neutrosophic set and Diophatine fuzzy set (DioFS). We discuss Diophantine neutrosophic weighted averaging (DioNWA), Diophantine neutrosophic weighted geometric (DioNWG), generalized Diophantine neutrosophic weighted averaging(GDioNWA), generalized Diophantine neutrosophic weighted geometric (GDioNWG). In this article, we define the Euclidean distance (ED), Hamming distance (HD) and operator laws. By analyzing new type of Diophantine neutrosophic set through algebraic operations, we discuss its properties.

CODAS method for Pythagorean 2-tuple linguistic multiple attribute group decision making

The evaluation of the financial performance of universities is conducive to the sustainable development of universities. Based on this, we extend the traditional CODAS (COmbinative Distance-based ASsessment) method to the Pythagorean 2-tuple linguistic fuzzy environment and propose a P2TL-CODAS model to evaluate the financial management performance of universities. Firstly, we briefly describe the definition, the score function, accuracy function, operational laws and the distance calculating method of P2TLSs. Next, two aggregation operators of P2TL including Pythagorean 2-tuple linguistic weighted averaging (P2TLWA) operator and Pythagorean 2-tuple linguistic weighted geometric (P2TLWG) operator are also introduced to fuse overall Pythagorean 2-tuple linguistic evaluation information. Then the steps of CODAS method are depicted briefly. Moreover, we use linguistic Pythagorean 2-tuple linguistic fuzzy numbers to extend the CODAS method. The P2TL-CODAS model is established and all computing steps are simply presented. Furthermore, we apply the proposed method to evaluate the financial management performance about five universities. Finally, a comparison between P2TL-CODAS method and P2TL-TODIM method is made to demonstrate the stability of the new method. The results show that the proposed method has unique advantages.

Target Damage Assessment Method Based on Interval‐Valued Intuitionistic Fuzzy Aggregation Operator under Dynamic Multi‐Expert

This study aims to solve the problem that the current target damage assessment method does not fully take into account the time series characteristics of the target and the dynamic changes in the battlefield situation, thus leading to insufficient accuracy of the assessment results. Target damage assessment method based on interval‐valued intuitionistic fuzzy aggregation operator (IVIFAO) under dynamic multi‐experts is a combination of interval‐valued intuitionistic fuzzy set (IVIFS) theory and dynamic multi‐attribute swarm decision‐making theory. Firstly, we extracted the effective factors that cause damage to the target and established the damage assessment index system. Secondly, in order to take into account the subjective weights and objective weights, we proposed a comprehensive weight model of damage factors based on interval‐valued intuitionistic fuzzy entropy (IVIFE) based on a cosine function (IVIFECF). The spatio‐temporal weights for each moment are determined using the Poisson distribution method. Then, given the inherent ambiguity and complexity of the decision‐making process, the decision‐making information is represented by interval‐valued intuitionistic fuzzy numbers (IVIFNs). We constructed a weighted interval‐valued intuitionistic fuzzy (WIVIF) decision matrix. Here, the interval‐valued intuitionistic fuzzy weighted geometric average (IVIFPWGA) operator is used to synthesize decision‐making information related to damage factors. We further introduce the dynamic interval‐valued intuitionistic fuzzy power‐weighted geometric average (DIVIFPWGA) operator, which combines instantaneous decision information with time series weights to generate a dynamic multi‐expert fusion WIVIF decision matrix. Finally, the improved TOPSIS method is used to rank the IVIFNs, resulting in a comprehensive damage assessment of the targets, which is analysed for superiority with the novel method, comparing both real‐time and scalability. The stability and validity of the method were verified.

Stepping Up: Education Department Installs Biometric System to Ensure Based on Complex T-Spherical Hesitant Fuzzy Aczel-Alsina Aggregation Operators

Stepping Up: Education Department Installs Biometric System to Ensure Based on Complex T-Spherical Hesitant Fuzzy Aczel-Alsina Aggregation Operators

TOPSIS method based on q-rung orthopair picture fuzzy soft environment and its application in the context of green supply chain management

<abstract> <p>Green supplier selection has been an important technique for environmental sustainability and reducing the harm of ecosystems. In the current climate, green supply chain management (GSCM) is imperative for maintaining environmental compliance and commercial growth. To handle the change related to environmental concern and how the company manages and operates, they are integrated the GSCM into traditional supplier selection process. The main aims of this study were to outline both traditional and environmental criteria for selecting suppliers, providing a comprehensive framework to assist decision-maker in prioritizing green supplier effectively. In order to address issue to simulate decision-making problems and manage inaccurate data. A useful technique of fuzzy set was proposed to handle uncertainty in various real-life problems, but all types of data could not be handled such as incomplete and indeterminate. However, several extensions of fuzzy set were considered, such as intuitionistic fuzzy set, Pythagorean fuzzy set, q-rung orthopair fuzzy set, and q-rung orthopair fuzzy soft set considering membership and nonmember ship grade to handle the uncertainty problem. However, there was a lack of information about the neutral degree and parameterization axioms lifted by existing approaches, so to fill this gap and overcome the difficulties Ali et al. proposed a generalized structure by combining the structure of picture fuzzy set and q-rung orthopair fuzzy soft set, known as q-rung orthopair picture fuzzy soft sets, characterized by positive, neutral and negative membership degree with parameterization tools and aggregation operator to solve the multi criteria group decision-making problem. Additionally, the TOPSIS method is a widely utilized to assist individuals and organizations in selecting the most appropriate option from a range of choices, taking into account various criteria. Finally, we demonstrate an illustrative example related to GSCM to enhance competitiveness, based on criteria both in general and with a focus on environmental consideration, accompanied by an algorithm and flow chart.</p> </abstract>

Optimal Single-Valued Neutrosophic Sine Trigonometric Aggregation Operators for Accurate Financial Fraud Detection Model

Financial fraud may be regarded as any fraud targeting financial organisations including crypto exchanges, banks, fintech, and lending organizations, or any criminal activity associated with the payment process. Financial fraud detection cites protocol set prepared to circumvent the destruction produced by fraudulent activities happening in financial service suppliers. Ecological financial fraud detection (FD) includes the usage of ethical and sustainable performs within fraud actions recognition from the financial area. In recent times, DL and ML techniques have been used in CCF recognition owing to their ability to construct a robust mechanism to discover fraud businesses. Therefore, this study develops an Optimal Single Valued Neutrosophic Sine Trigonometric Aggregation Operator (O-SVNSTAO) for Accurate Financial Fraud Detection Model. The genetic-inspired particle swarm optimization (GIPSO) feature selection model efficiently discerns the relevant attribute from sophisticated financial databases, improving the model's discriminative power while alleviating dimensionality problems. Consequently, the SVNSTAO classifier leverages the features selected to discern complicated features inherent in fraudulent actions, which facilitates accurate diagnosis. Moreover, the COA parameter tuning mechanism enhances the SVNSTAO model's parameter, which ensures adaptability and optimum performance to varied fraud settings. Empirical analysis of real-time financial datasets demonstrates the superiority of O-SVNSTAO technique over classical methods, underlining its effectiveness in discovering financial fraud with exceptional efficiency and reliability

Confidence Levels-Based p, q, r–Spherical Fuzzy Aggregation Operators and Their Application in Selection of Solar Panels

Confidence Levels-Based <i>p</i>, <i>q</i>, <i>r</i>–Spherical Fuzzy Aggregation Operators and Their Application in Selection of Solar Panels

Parameter Selection Impacting Software Reliability by Utilizing WASPAS Technique Based on Tangent Trigonometric Complex Fuzzy Aggregation Operators

Parameter Selection Impacting Software Reliability by Utilizing WASPAS Technique Based on Tangent Trigonometric Complex Fuzzy Aggregation Operators

Confidence Levels Bipolar Complex Fuzzy Aggregation Operators and Their Application in Decision Making Problem

Confidence Levels Bipolar Complex Fuzzy Aggregation Operators and Their Application in Decision Making Problem

Conditional Aggregation Operator Defined by the Power Information Concerning Type-2 Fuzzy Deep Learning Algorithm for Financial Investment Data Decision-Making

Conditional Aggregation Operator Defined by the Power Information Concerning Type-2 Fuzzy Deep Learning Algorithm for Financial Investment Data Decision-Making

Design of a Business Sustainability Measurement Method for Based on NeutroAlgebras Generated by the Combining Function in Prospector and Neutrosophic 2-tuple Linguistic Models

Business sustainability has become a global imperative in response to the environmental, social, and economic challenges facing our world. In this context, the measurement and evaluation of business sustainability have become crucial to guide the actions of organizations towards more responsible and sustainable practices. However, the lack of specific measurement instruments for specific regional contexts may limit the ability of companies to evaluate and improve their sustainability performance. In this paper, we present the design of a business sustainability meas-urement method adapted to the context of Tarma, Peru. Tarma, a region located in the heart of the Peruvian Andes, is characterized by its cultural, environmental, and economic diversity, making it a unique context to address busi-ness sustainability. This article proposes a method for measuring business sustainability based on the Neutrosophic 2-tuple Linguistic Model, which includes an aggregation operation based on a NeutroAlgebra generated by Combin-ing Functions in Prospector.

Rough Neutrosophic Multisets Geometric Aggregation Operator with Entropy Weight Combined Roughness Dice Similarity Measure and Its Application

Rough Neutrosophic Multisets Geometric Aggregation Operator with Entropy Weight Combined Roughness Dice Similarity Measure and Its Application

Evaluation Based on Distance From Average Solution for Circular Pythagorean Fuzzy Schweizer-Sklar Power Aggregation Operators and Their Application in Transportation Problems for Linear Programming

Evaluation Based on Distance From Average Solution for Circular Pythagorean Fuzzy Schweizer-Sklar Power Aggregation Operators and Their Application in Transportation Problems for Linear Programming

Selection of Energy Trading Platform for Peer-to-Peer (P2P) Energy Trading by Using a Multi-Attribute Decision-Making Approach Based on Bipolar Fuzzy Aczel-Alsina Prioritized Aggregation Operators

Selection of Energy Trading Platform for Peer-to-Peer (P2P) Energy Trading by Using a Multi-Attribute Decision-Making Approach Based on Bipolar Fuzzy Aczel-Alsina Prioritized Aggregation Operators

Analysis and Applications of Bipolar Complex Fuzzy Soft Power Dombi Aggregation Operators for Robot Selection in Artificial Intelligence

Analysis and Applications of Bipolar Complex Fuzzy Soft Power Dombi Aggregation Operators for Robot Selection in Artificial Intelligence