Single-valued Neutrosophic Set Research Articles

Health Insurance Provider Selection Through Novel Correlation Measure of Neutrosophic Sets Using TOPSIS

Risk monitoring aims to recognize and control potential threats to our assets or health activities. Insurance is vital, as it compensates for any unexpected loss of property or life. Clients selecting the best health insurance provider must consider various factors and their relative significance to their circumstances. Multi-criteria decision-making (MCDM) helps people analyze and compare policy alternatives to find the best option. This research aims to assist potential health policy purchasers by addressing the selection of health insurance providers as an MCDM problem. The correlation coefficient is useful for identifying the importance of several conflicting criteria. The idea of correlation coefficients is extended in a neutrosophic context to capture the indeterminacy and incomplete information in the relationship among the criteria. The technique for order preference by similarity to an ideal solution (TOPSIS) approach is a useful and straightforward approach to solving MCDM problems. However, it often became ambiguous to researchers due to its involvement in the distance measure technique. The proposed neutrosophic correlation measure may also replace the ambiguity of using a suitable distance measure in the TOPSIS approach. This study extends the TOPSIS method by using the proposed neutrosophic correlation coefficient on single-valued neutrosophic sets (SVNSs). The criteria preferences are computed using a method based on the removal effects of the criteria (MEREC) approach. Some valuable concepts, like the weighted closeness measure of type I and type II and the weighted index parameter, are introduced with their properties to establish the proposed neutrosophic TOPSIS approach. An MCDM approach for health insurance providers has been constructed to illustrate the proposed approach numerically. The proposed method suggest that the health insurance provider ϒ2 is the most beneficial alternative, whereas ϒ1 is the least suitable. The client considers the terms and conditions for non-coverage and the facilities provided for pediatric and maternity care while buying health insurance. The comparative analysis of the suggested technique demonstrates the merit of the research in terms of consistency. The sensitivity analysis demonstrates the flexibility and robustness of the obtained results.

An Approach to Multi-Attribute Decision-Making Based on Single-Valued Neutrosophic Hesitant Fuzzy Aczel-Alsina Aggregation Operator

A single-valued Neutrosophic hesitant fuzzy set (SVNHFS) is a combination of a single-valued neutrosophic set (SVNS) and hesitant fuzzy set (HFS) that has been developed to address insufficient, unreliable, and vague environments in which each element has several possible options determined by the truthiness, indeterminacy and falsity value. By considering this, in this paper, we have proposed the Aczel-Alsina aggregation operator (AAAO) for SVNHFS, which is more flexible t-norm and t-conorm than the other and due to the flexible nature of parameters to solve Multi-Attribute decision making (MADM) problems. Further, the score function, accuracy function, and certainty function of SVNHFS have been defined. In this paper, we proposed the single-valued neutrosophic hesitant fuzzy Aczel-Alsina Weighted Averaging Operator (SVNHFAAWA), single-valued neutrosophic hesitant fuzzy Aczel-Alsina Weighted ordered Averaging Operator (SVNHFAAWOA), and single-valued neutrosophic hesitant fuzzy Aczel-Alsina hybrid averaging operator (SVNHFAAHA). To testify to the reliability and stability of the newly created aggregation operator (AO), an application of MADM has been discussed.

Divergence Measures and Aggregation Operators for Single-Valued Neutrosophic Sets with Applications in Decision-Making Problems

Divergence Measures and Aggregation Operators for Single-Valued Neutrosophic Sets with Applications in Decision-Making Problems

Multi Criteria Decision Making Under Single-Valued Neutrosophic Set Environment for Supplier Selection

Multi Criteria Decision Making Under Single-Valued Neutrosophic Set Environment for Supplier Selection

Fuzzy risk analysis in crop selection using information measures on quadripartitioned single-valued neutrosophic sets

Crop selection is a critical task that involves assessing multiple risk factors to achieve maximum yield. Therefore, risk assessment plays a pivotal role in choosing suitable crops for cultivation. Probabilistic and possibilistic methods are the two primary approaches used for the crop selection process. Probabilistic methods are cost-intensive due to data handling, while possibilistic methods, utilizing linguistic variables, are considered more reliable. In this article, we represent such linguistic variables using Quadripartitioned Single-Valued Neutrosophic Sets (QSVNSs), extensions of Single-Valued Neutrosophic Sets (SVNSs) characterized by four independent membership functions that enhance uncertainty accommodation. We propose two QSVNS-based information measures, entropy and similarity, to transform the final risks evaluated in the form of QSVNSs into linguistic variables for easier comprehension by the general audience. We apply this framework to mustard and paddy cultivation in Assam, a state located in northeastern India, conducting thorough analyses and validation tests. Additionally, statistical tests are presented to demonstrate the significance of the obtained results. The final risk of mustard cultivation is found to be ‘absolutely high’, as the largest similarity value of 0.9910 is obtained for the linguistic term ‘absolutely high’ among all computed similarity value results. Similarly, for paddy cultivation, the largest similarity value of 0.9159 is obtained for the linguistic term ‘very low’, indicating its final risk in our assumed scenario. Thus, the veracity and proficiency of our newly constructed measures are reflected in their practical applications.

An extended power geometric technique for multiple-attribute decision-making under single-valued neutrosophic sets and applications to embedded computers’ performance evaluation

An extended power geometric technique for multiple-attribute decision-making under single-valued neutrosophic sets and applications to embedded computers’ performance evaluation

Multi-attribute decision-making problem in career determination using single-valued neutrosophic distance measure

In this paper, we introduce a distance measure on single-valued neutrosophic sets by sine function which is a generalization of intuitionistic fuzzy sine distance measure. The axiom of metric on single-valued neutrosophic sets is verified and shows that the difference of distance measure from unity is a similarity measure. A new methodology for multi-attribute decision-making problems (MADM) is developed for the most common decision by the smallest measure value of the proposed single-valued neutrosophic distance measure. We further apply this distance measure to a multi-attribute decision-making problem (MADM) for student career determination in a neutrosophic environment to find the best career for suitable students. Finally, the comparison is made between the proposed distance measure and the other distance measures for the final decision chosen from the most common decisions of them.

Multi-criteria decision-making based on Einstein operators, WASPAS method and quadripartitioned single-valued neutrosophic sets

Multi-criteria decision-making based on Einstein operators, WASPAS method and quadripartitioned single-valued neutrosophic sets

A Combined Decision-Making Analysis Under Single-Valued Neutrosophic Set for Selecting Favorable Knowledge Management Strategy

The Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are pivotal methods in multi-criteria decision-making, addressing causal relationships among criteria and ranking alternatives, respectively. This paper introduces a novel approach, integrating DEMATEL and TOPSIS under the framework of single-valued neutrosophic set (SVNS) to handle indeterminacy in decision-making. Applied to a knowledge management strategy case, the method utilizes eight criteria and four alternatives derived from the literature. The process involves DEMATEL for expert weight determination and direct-relation matrix creation through linguistic variable influence. Subsequently, TOPSIS is employed to rank alternatives based on distance measures. The combined method identifies the ‘Human Resource Department’ as the most crucial in knowledge management strategy. This integrated approach facilitates organizations in pinpointing vital criteria and alternatives for effective knowledge management. Comparative analyses with existing methods are also presented.

A novel framework for single-valued neutrosophic MADM and applications to English-blended teaching quality evaluation

Abstract In the context of “Internet plus,” college English-teaching resources are increasingly rich. Research has found that implementing a blended teaching model for college English based on the Super Star Learning Communication and Rain Classroom online teaching platform is beneficial for improving students’ enthusiasm and continuity in English learning. The English-blended teaching quality evaluation is a multiple attribute decision making (MADM). The single-valued neutrosophic set (SVNS) is a useful tool to depict uncertain information during the English-blended teaching quality evaluation. In such an article, the single-valued neutrosophic number Aczel–Alsina power geometric (SVNNAAPG) operator is produced based on the Aczel–Alsina operations and classical power geometric operator under SVNSs. The SVNNAAPG operator is built for MADM. Eventually, an example about English-blended teaching quality evaluation and some selected comparative analysis was used to depict the SVNNAAPG technique.

Aggregation operators-based divergence measures for single-valued neutrosophic sets with their applications to pattern recognition

A Single-valued neutrosophic set (SVNS) has recently been explored as a comprehensive tool to assess uncertain information due to varied human cognition. This notion stretches the domain of application of the classical fuzzy set and its extended versions. Various comparison measures based on SVNSs like distance measure, similarity measure, and, divergence measure have practical significance in the study of clustering analysis, pattern recognition, machine learning, and computer vision-related problems. Existing measures have some drawbacks in terms of precision and exclusion of information and produce unreasonable results in categorization problems. In this paper, we propose a generic method to define new divergence measures based on common aggregation operators and discuss some algebraic properties of the proposed divergence measures. To further appreciate the proposed divergence measures, their application to pattern recognition has been investigated in conjunction with the prominent existing comparison measures based on SVNSs. The comparative assessment sensitivity analysis of the proposed measures establishes their edge over the existing ones because of appropriate classification results.

A Novel Approach on Energy of λJ-dominating Single-Valued Neutrosophic Graph Structure

The concept of dominance is one of the most important ideas in graph theory for handling random events, and it has drawn the interest from many scholars. Research related to graph energy has garnered a lot focus recently. The application of single-valued neutrosophic graphs (SVNGs) for energy, Laplacian energy, and dominating energy has been recommended by previous studies. In this research, we apply the concepts of single-valued neutrosophic sets (SVNS) to graph structures (GSs) and investigate some intriguing features of single-valued neutrosophic graph structures (SVNGS). Moreover, the notions of λJ-dominating energy GS in an SVNGS environment are analyzed in this study. More specifically, illustrative examples are used to develop the adjacency matrix of a λJ-dominating SVNGS, as well as the spectrum of the adjacency matrix and their related theory. Further, the SVNGS λJ-dominating energy is determined. We go over various characteristics and constraints for the energy of SVNGS with λJ-dominating. Further, we introduce the idea of isomorphic and identical λJ-dominating SVNGS energy, which has been studied using relevant examples, and some of its established properties are presented.

A three-way decision method on multi-scale single-valued neutrosophic decision systems

In this paper, we propose a three-way decision (TWD) method on multi-scale single-valued neutrosophic decision systems (MS-SVNDSs). First, to explore the application of single-valued neutrosophic sets (SVNSs) in multi-scale environment, we establish a rough set model of MS-SVNDSs. Then, aiming at the problem of knowledge acquisition in MS-SVNDSs, we present the corresponding optimal scale selection and reduction methods by using evidence theory, a more direct and simpler algorithm is also discussed. For obtaining decision results that are more in line with human cognition, we further provide a novel three-way decision method. Comparative experiments are subsequently conducted to demonstrate the effectiveness of our approach. The experimental results show that our method not only improves the classification accuracy but also raises decision efficiency.

The Enduring Power of Giving and Caring from Cavemen to Kind Hearts: A Neutrosophic Multi-Criteria Decision Making Approach

Giving and caring are not just warm and fuzzy feelings; they are the bedrock of a healthy society. By understanding the neuroscience and sociology behind these behaviors, we can cultivate a world that prioritizes cooperation, compassion, and the well-being of all its members. We used the single valued neutrosophic sets (SVNSs) with the multi-criteria decision making (MCDM) method for evaluating the giving and caring impacts. We used TreeSoft to divide the problems as a tree. The SVNSs were used to overcome uncertain information in the evaluation process. The SVNSs were integrated with the DEMATEL method to compute the relationships between criteria. This study used nine criteria. The results show the criterion 5 has the highest impacts and criterion 1 has the lowest criterion.

Decision Support System for Single-Valued Neutrosophic Aczel–Alsina Aggregation Operators Based on Known Weights

Multiattribute decision making (MADM) approach is a well-known decision-making process utilized in a variety of fields such as solid waste management, renewable energy resources, air quality assurance, hotel location decision, sustainable supplier selection, partner recognition, green supplier enterprises, game theory, construction development authority, and weapon group target estimation. The aggregation operators (AOs) are essential components of the decision-making process and have a great capability to deal with ambiguous and unpredictable information in the different fields of fuzzy environments. In this article, we expressed the theory concepts of single-valued neutrosophic (SVN) sets (SVNS) and also characterized their basic operations. The power aggregation tools are allowed to input arguments to support each other among different arguments. Recently, Aczel–Alisna aggregation tools conquered great attention from several research scholars. We also exposed some reliable operations of Aczel–Alsina aggregation models under the consideration of SVN information. We established a series of new approaches, including the “single-valued neutrosophic Aczel–Alsina power weighted average” (SVNAAPWA) operator and “single-valued neutrosophic Aczel–Alsina power weighted geometric” (SVNAAPWG) operators. To show the effectiveness and compatibility of derived approaches, some prominent characteristics are also established. We constructed a MADM technique to solve an application of engineering and construction materials under consideration of our derived methodologies. An experimental case study is also presented to determine a suitable optimal option from a group of options. To find the flexibility of our proposed work, we provided a comparative study that compares the results of existing AOs with our proposed work. A comprehensive overview is also presented here.

Single-Valued Neutrosophic Sets Based Score Function and WASPAS Method for Plant Location Selection Problem

In the context of single-valued neutrosophic sets (SVNSs), where the weights of the criteria are unknown, this work seeks to provide an integrated technique based on Entropy and Weighted Aggregate Sum Product Assessment (WASPAS) methodologies. A numerical case study (the plant site selection issue) is used to establish precise values for the criteria. We initially "fuzzify" the decision matrix before transforming it into an SVNS- decision matrix. The SVNS entropy weight technique is used to assign weights to each criterion. The scoring function is used by a tweaked version of the WASPAS algorithm to choose the optimal solution. The subject under study has also been applied to other MCDM methods, such as the more prevalent VIKOR and MOORA procedures. The SVNS-VIKOR technique has also been applied to the issue at hand. Using the same illustrative scenario, this study evaluates the strengths and weaknesses of several methods for verifying the accuracy of previously published data. The usefulness and efficiency of the used strategy are highlighted by the comparison study. When applied to real-world situations, the suggested method shines because it yields reliable findings even though the underlying data is plagued with issues such as uncertainty, imprecision, indeterminacy, and inconsistency.

Bi-objective optimization of an EDM process with Cu-MWCNT composite tool using single-valued neutrosophic grey relational analysis

Purpose In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode. Design/methodology/approach This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool. Findings It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm3/min and 0.001034 g/min, respectively. Originality/value Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

LogTODIM framework for MAGDM with neutrosophic sets: Energy conservation and emission reduction case

The significant acceleration of China’s urbanization process has greatly promoted economic development. At the same time, the massive construction of urban buildings has also caused many problems such as environmental pollution and increased energy consumption. Therefore, in architectural design, it is particularly important to pay attention to the sustainable development of the environment, handle the relationship between good people and nature under the guidance of the concept of green development, and focus on the recycling of resources. Focusing on resource utilization in architectural design and based on certain planning can better control the construction process of urban buildings, save energy consumption, reduce construction costs, and contribute to the green development of cities. The comprehensive evaluation of energy conservation and emission reduction of construction projects is a classical MAGDM problems. Recently, the Logarithmic TODIM (LogTODIM) method has been employed to cope with MAGDM issues. The single-valued neutrosophic sets (SVNSs) are used as a tool for characterizing uncertain information during the comprehensive evaluation of energy conservation and emission reduction of construction projects. In this paper, the single-valued neutrosophic number Logarithmic TODIM (SVNN-LogTODIM) method is built to solve the MAGDM under SVNSs. In the end, a numerical case study for comprehensive evaluation of energy conservation and emission reduction of construction projects is given to validate the proposed method.

Multi-attribute decision-making methods based on Aczel-Alsina power aggregation operators for English blended teaching quality evaluation under single-valued neutrosophic sets

As a new form of teaching, blended teaching can integrate the advantages of classroom teaching and online teaching and improve the overall quality and effectiveness of English teaching under the premise of changing the orientation of teachers and students. The English blended teaching quality evaluation is a multiple attribute decision making (MADM) issue. Aczel-Alsina t-norm and t-conorm operations have the true advantage of changeability by adjusting a decision parameter. power averaging (PA) operator allowed decision attributes to strengthen each other through weight information during fusion, thereby eliminating the influence of subjective weights on the decision results. Motivate through classical Aczel-Alsina operators, PA operator and the single-valued neutrosophic sets (SVNSs), in this paper, the single-valued neutrosophic number Aczel-Alsina power averaging (SVNNAAPA) operator and the single-valued neutrosophic number Aczel-Alsina power weighted averaging (SVNNAAPWA) operator are constructed under SVNSs. The SVNNAAPWA operator is built for MADM. Eventually, an example about English blended teaching quality evaluation and some selected comparative decision analysis is used to depict the SVNNAAPWA method.

A single-valued neutrosophic CIMAS-CRITIC-RBNAR decision support model for the financial performance analysis: A study of technology companies

Financial performance stands as a fundamental performance indicator that reflects companies' current financial conditions, providing information to investors and stakeholders about companies' financial well-being. In this research, a decision support system is developed for identifying the financial performance of companies traded on stock exchanges. This decision support system is based on a multicriteria decision-making (MCDM) approach and neutrosophic logic. The research introduces a novel method for calculating and ranking financial performance, using financial ratio indicators as selection criteria. The importance levels of financial ratio indicators are weighted through two different approaches. In the first approach, expert opinions and criteria importance assessment (CIMAS)-based on single-valued neutrosophic (SVN) sets are utilized for calculation. In the second approach, criteria importance through intercriteria correlation (CRITIC)-based on reference-based normalization processes is employed for criteria weighting. Subsequently, the results of the two criterion weightings are combined to calculate the final criterion weights. The SVN reference-based normalization alternative ranking (RBNAR) method is presented for ranking companies based on their financial performance. Thus, SVN-CIMAS-CRITIC-RBNAR is developed and its algorithm is presented. The novel hybrid decision support model is applied to a case study of technology companies traded on the Borsa Istanbul. The research results support the applicability of the SVN-CIMAS-CRITIC-RBNAR hybrid method. The results of the case study and sensitivity analyses affirm the applicability and robustness of the SVN-CIMAS-CRITIC-RBNAR hybrid model. The research provides detailed implications and insights for financial managers.