Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this article.Adescription is provided of the scoring function,accuracy function and operational laws of the log q-rung VS.The algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming distance.Additionally,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization.We chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile amnesia.Natural numbers q are used to express the results of the models.To demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.

Fuzzy description logic based on vague sets

To enable the representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web, a new fuzzy extension of description logics called vague ALC which is based on vague sets is presented. The definition of vague set is introduced and then the syntax and semantics of vague ALC are formally defined. The forms of axioms and assertions in the vague ALC knowledge bases are specified. Finally, the tableau algorithm is developed for the reasoning in the vague ALC. The vague ALC based on vague set uses two degrees of membership instead of a single membership degree in the fuzzy sets and is more accurate in representing the imprecision in the degrees of membership. The vague ALC has more expressive power than ALC and can represent fuzzy knowledge and perform reasoning tasks based on them. Therefore, the vague ALC can enable the representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web.

Optimal Route Selection Method Based on Vague Sets

Optimal route selection is an important function of vehicle trac flow guidance system. Its core is to determine the index weight for measuring the route merits and to determine the evaluation method for selecting route. In this paper, subjective weighting method which relies on driver preference is used to determine the weight and the paper proposes the multi-criteria weighted decision method based on vague sets for selecting the optimal route. Examples show that, the usage of vague sets to describe route index value can provide more decision-making information for route selection.

A Vague Set Based OWA Method for Talent Evaluation

In recent years,decision-making under uncertainty has attracted substantial attention in both academia and industry,with a growing number of organizations prioritizing decision support for talent evaluation.Vague set theory has been recognized as a powerful tool to address the ambiguity of problem parameters and manage uncertainty.This paper introduces a novel talent evaluation method that harnesses the potential of vague sets.We construct a vague set Ordered Weighted Averaging(OWA)operator for offering a robust solution to intricate decision-making problems,especially in talent evaluation.The application of the OWA operator augments the decision-making process by providing a mechanism to handle the aggregation of information in a more flexible and comprehensive manner.Experimental results show the effectiveness of the proposed method,presenting an alternative for decision-makers,aiding them in selecting their preferred choices amidst uncertainty.

A vague-set-based fuzzy multi-objective decision making model for bidding purchase

A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.

Approximation operators based on vague relations and roughness measures of vague sets

Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy set model based on fuzzy relations to vague sets. We mainly focus on the lower and upper approxima- tion operators of vague sets based on vague relations, and investigate the basic properties of approximation opera- tors on vague sets. Specially, we give some essential characterizations of the lower and upper approximation operators generated by reflexive, symmetric, and transi- tive vague relations. Finally, we structure a parameterized roughness measure of vague sets and similarity measure methods between two rough vague sets, and obtain some properties of the roughness measure and similarity measures. We also give some valuable counterexamples and point out some false properties of the roughness measure in the paper of Wang et al.

Eigenvector Method for Ranking Alternatives with Vague Value Measurements

An eigenvector method for ranking alternatives whose measurements are given as vague values is provided. Firstly, a positive matrix is constructed which is defined as evaluation information matrix （EIM）. Based on four assumptions for evaluating alternatives, a ranking eigenvector is defined. And then it is proved, based on positive matrix theory, that the EIM＇s eigenvector corresponding to the maximal eigenvalue is the ranking vector. For alternatives whose characteristics are presented by vague sets, the proposed techniques can evaluate the degree of suitability to which an alternative satisfies the decision-maker＇ s requirement efficiently.

Research on the dynamic andnon-same-plane vague region relations without kernel

To remedy the defects of the existing research achievements,the dynamic vague region relations without kernel and the non-same-plane vague region relations without kernel based on the conception of the vague sets were studied systematically.The formalized definitions of the vague intersection set,the vague cut sets and vague region partition etc were given.Based on the vague sets,the eight vague region relations in the same plane and the ten vague region relations in the different plane were given.Furthermore,the coessential intersection and the heterogeneous intersection were proposed to simplify the representation for the dynamic vague region relations without kernel and the rotation-corresponding relations between the two kinds of the relations were also studied.The production in this paper laid the foundation for the applications and research of the vague region relations without kernel in the spatial database.

A New Approach to Vague Soft Bi-Topological Spaces

Fuzzy soft topology considers only membership value.It has nothing to do with the non-membership value.So an extension was needed in this direction.Vague soft topology addresses bothmembership and non-membership values simultaneously.Sometimes vague soft topology(single structure)is unable to address some complex structures.So an extension to vague soft bi-topology(double structure)was needed in this direction.To make this situation more meaningful,a new concept of vague soft bi-topological space is introduced and its structural characteristics are attempted with a new definition.In this article,new concept of vague soft bi-topological space(VSBTS)is initiated and its structural behaviors are attempted.This approach is based on generalized vague soft open sets,known as vague softβopen sets.An ample of examples are given to understand the structures.For the non-validity of some results,counter examples are provided to pay the price.Pair-wise vague softβopen and pair-wise vague softβclose sets are alsoaddressedwith examples in(VSBTS).Vague soft separation axioms are initiatedin(VSBTS)concerning soft points of the space.Other separation axioms are also addressed relative to soft points of the space.Vague soft bi-topological properties are studied with the application of vague softβopen sets with respect to soft points of the spaces.The characterization of vague softβclose as well as vague softβopen sets,characteristics of Bolzano Weirstrass property,vague soft compactness and its marriage with sequences,interconnection between sequential compactness and countable compactness in(VSBTS)with respect to softβopen sets are addressed.

The Applications of Vague Soft Sets and Generalized Vague Soft Sets

The problem of decision making in an imprecise environment has found paramount importance in recent years. In this paper, we define vague soft relation and similarity measure of vague soft sets. Using these definitions, some novel methods of object recognition from an imprecise multiobserver data has been presented. Moreover, we introduce the notion of generalized vague soft sets and study some of its properties. The similarity measure of generalized vague soft sets is also presented and an application of this measure in decision making problems has been shown.

A Vague Decision Method for Analog Circuit Fault Diagnosis Based on Description Sphere

This paper proposes a vague decision method for analog circuit fault diagnosis based on description sphere. Firstly, the proposed method uses the wavelet transform as the preprocessor to extract fault features from the output voltages of the circuit un- der test （CUT）. And then, each class sample is trained to produce a minimum description sphere. Finally, the test samples are detected by a defined vague decision rule, which is based on the vague weight distance between the test data and the center of description sphere. The defined decision rule fuses the truth and false membership degrees of the test sample and the weight of the description sphere, and it can effectively deal with the uncertain information. The reliability of the defined decision rule is proved theoretically. This new diagnostic method is first applied to testing two actual circuits, and then it is compared with other two diagnostic methods. The experimental results show that the proposed technique can achieve good performance and reduce the diagnostic time.

Nonempirical hybrid multi-attribute decision-making method for design for remanufacturing

Design for remanufacturing(DfRem)is the process of considering remanufacturing characteristics during product design in order to reduce the number of issues during the remanufacturing stage.This decisionmaking in DfRem is influenced by the designers'subjective preferences owing to a lack of explicitly defined remanufacturing knowledge for designers,which can lead to indecisive design schemes.In order to objectively select the optimal design scheme for remanufacturing,a nonempirical hybrid multi-attribute decision-making method is presented to alleviate the impacts of subjective factors.In this method,design characteristics and demand information are characterized through the matter-element theory.Coupled with design principles,some initial design schemes are proposed.Evaluation criteria are established considering the technical,economic,and environmental factors.The entropy weight and vague set are used to determine the optimal design scheme via a multi-attribute decision・making approach.The design of a bearing assembly machine for remanufacturing is taken as an example to illustrate the practicality and validity of the proposed method.The results revealed that the proposed method was effective in the decision-making of DfRem.