Dombi-Normalized Weighted Bonferroni Mean Operators with Novel Multiple-Valued Complex Neutrosophic Uncertain Linguistic Sets and Their Application in Decision Making

Although fuzzy set concepts have evolved,neutrosophic sets are attractingmore attention due to the greater power of the structure of neutrosophic sets.The ability to account for components that are true,false or neither true nor false is useful in the resolution of real-life problems.However,simultaneous variations render neutrosophic sets unsuitable in specific circumstances.To enable the management of these sorts of issues,we combine the principle of multi-valued neutrosophic uncertain linguistic sets and complex fuzzy sets to develop the principle of multivalued complex neutrosophic uncertain linguistic sets.Multi-valued complex neutrosophic uncertain linguistic sets can contain grades of truth,abstinence,and falsity,and uncertain linguistic terms,which are expressed as complex numbers whose real and imaginary parts are limited to the unit interval.Some important Dombi laws are elaborated along with Bonferroni mean operators,which offer a flexible general structure with modifiable factors.Bonferroni means aggregation operators perform a significant role in conveying the magnitude level of options and characteristics.To determine relationships among any number of attributes,we develop multi-valued complex neutrosophic uncertain linguistic Dombi-normalized weighted Bonferroni mean operators and discuss their important properties with some special cases.By using these laws,we can deploy themulti-attribute decisionmaking(MADM)technique using the novel principle of multi-valued complex neutrosophic uncertain linguistic sets.To determine the power and flexibility of the elaborated approach,we resolve some numerical examples based on the proposed operator.Finally,the work is validated with the help of comparative analysis,a discussion of its advantages,and geometric expressions of the elaborated theories.

Some interval-valued intuitionistic uncertain linguistic hybrid Shapley operators

Two interval-valued intuitionistic uncertain linguistic hybrid operators cal ed the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley averaging （I-IIULHSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid Shapley geometric （I-IIULHSG） operator are defined. These operators not only reflect the importance of elements and their ordered positions, but also consider the correlations among elements and their ordered positions. Since the fuzzy measures are defined on the power set, it makes the problem exponentially complex. In order to simplify the complexity of solving a fuzzy measure, we further define the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley averaging （I-IIULHλSA） operator and the induced interval-valued intuitionistic uncertain linguistic hybrid λ-Shapley geometric （I-IIULHλSG） operator. Moreover, an approach for multi-attribute group decision making under the interval-valued intuitionistic uncertain linguistic environment is developed. Finally, a numerical example is provided to verify the developed procedure and demonstrate its practicality and feasibility.

Interactive group decision making procedure based on uncertain multiplicative linguistic preference relations

Group decision making problems are investigated with uncertain multiplicative linguistic preference relations.An unbalanced multiplicative linguistic label set is introduced,which can be used by the experts to express their linguistic preference information over alternatives.The uncertain linguistic weighted geometric mean operator is utilized to aggregate all the individual uncertain multiplicative linguistic preference relations into a collective one,and then a simple approach is developed to determine the experts＇ weights by utilizing the consensus degrees among the individual uncertain multiplicative linguistic preference relations and the collective uncertain multiplicative linguistic preference relations.Furthermore,a practical interactive procedure for group decision making is proposed based on uncertain multiplicative linguistic preference relations,in which a possibility degree formula and a complementary matrix are used to rank the given alternatives.Finally,the proposed procedure is applied to solve the group decision making problem of a manufacturing company searching the best global supplier for one of its most critical parts used in assembling process.

Top-k probabilistic prevalent co-location mining in spatially uncertain data sets

A co-location pattern is a set of spatial features whose instances frequently appear in a spatial neighborhood. This paper efficiently mines the top-k probabilistic prevalent co-locations over spatially uncertain data sets and makes the following contributions： 1） the concept of the top-k prob- abilistic prevalent co-locations based on a possible world model is defined; 2） a framework for discovering the top- k probabilistic prevalent co-locations is set up; 3） a matrix method is proposed to improve the computation of the preva- lence probability of a top-k candidate, and two pruning rules of the matrix block are given to accelerate the search for ex- act solutions; 4） a polynomial matrix is developed to further speed up the top-k candidate refinement process; 5） an ap- proximate algorithm with compensation factor is introduced so that relatively large quantity of data can be processed quickly. The efficiency of our proposed algorithms as well as the accuracy of the approximation algorithms is evaluated with an extensive set of experiments using both synthetic and real uncertain data sets.

MCGDM model using uncertain linguistic consistency sets of single andinterval linguistic term multivalued sets

This paper presents hybrid linguistic expressions and operations for the hybridlinguistic multiple criteria group decision making (MCGDM) issue withidentical and/or different single and interval linguistic term values. First, wepropose a single and interval linguistic term multivalued set/element (SILTMS/SILTME) and develop a consistency measure of SILTMEs based on Shannonentropy to measure the consistency degree of single and interval linguistic termvalues in SILTME. Second, we converse SILTMS/SILTME into an uncertainlinguistic consistency set/element (ULCS/ULCE) in terms of the mean andconsistency measure of SILTMEs to reasonably perform operations betweendifferent information forms/sequence lengths in SILTMSs. Third, we definesome operations of ULCEs and the expected values and sorting rules ofULCEs. Fourth, we present the ULCE weighted mean and geometric operatorsand their characteristics. Finally, we develop a MCGDM model using theweighted mean operation of the two operators and apply it in the mine safetyassessment.

Probabilistic uncertain linguistic TODIM method based on the generalized Choquet integral and its application

Purpose-The purpose of this paper is to develop a probabilistic uncertain linguistic(PUL)TODIM method based on the generalized Choquet integral,with respect to the interdependencies between criteria,for the selection of the best alternate in the context of multiple criteria group decision-making(MCGDM).Design/methodology/approach-Owing to decision makers(DMs)do not always show completely rational and may have the preference of bounded rational behavior,this may affect the result of the MCGDM.At the same time,criteria interaction is a focused issue in MCGDM.Hence,a novel TODIM method based on the generalized Choquet integral selects the best alternate using PUL evaluation,where the generalized Choquet integral is used to calculate the weight of criterion.The generalized PUL distance measure between two probabilistic uncertain linguistic elements(PULEs)is calculated and the perceived dominance degree matrices for each alternate relative to other alternates are obtained.Furthermore,the comprehensive perceived dominance degree of each alternate can be calculated to get the ranking.Findings-Potential application of the PUL-TODIM method is demonstrated through an evaluation example with sensitivity and comparative analysis.Originality/value-As per author’s concern,there are no TODIM methods with probabilistic uncertain linguistic sets(PULTSs)to solve MCGDM problems under uncertainty.Compared with the result of existing methods,the final judgment value of alternates using the extended TODIM methodology is highly corroborated,which proves its potential in solving MCGDM problems under qualitative and quantitative environments.