An interval‐valued exceedance method in MCDM with uncertain satisfactions

Liu, Zeyi; Xiao, Fuyuan

doi:10.1002/int.22171

Cited by 21 publications

(4 citation statements)

References 74 publications

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“…BUI can conveniently express the extent of uncertainty in decision-making, which helps one to make a reasonable evaluation and make wise decisions in uncertainty environment. Recently, apart from the authors of this work, other researchers also paid attention to BUI and developed its related theories, new concepts, and applications [37][38][39][40][41][42][43]. For example, Chen et al [37] proposed the Improved Basic Uncertain Linguistic Information (IBULI) as a new extension of BUI, and Tao et al [38] proposed basic uncertain information soft set with its application.…”

Section: Definition 1 the Weighted Average Operator With Weight Funct...mentioning

confidence: 99%

Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information

Jin

Chen

et al. 2022

Mathematics

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This paper elaborates the different methods to generate normalized weight vector in multi-criteria decision-making where the given information of both criteria and inputs are uncertain and can be expressed by basic uncertain information. Some general weight allocation paradigms are proposed in view of their convenience in expression. In multi-criteria decision-making, the given importance for each considered criterion may have different extents of uncertainty. Accordingly, we propose some special induced weight-allocation methods. The inputs can be also associated with varying uncertainty extents, and then we develop several induced weight-generation methods for consideration. In addition, we present some suggested and prescriptive weight allocation rules and analyze their reasonability.

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Section: Definition 1 the Weighted Average Operator With Weight Funct...mentioning

confidence: 99%

Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information

Jin

Chen

et al. 2022

Mathematics

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“…Mathematical expressions have a complex two-dimensional structure, so it is very reasonable to introduce multi-criteria decision-making (MCDM) theory in the retrieval of mathematical expressions. MCDM theory has made many advances in recent years [ 13 , 14 , 15 ], and has been applied and has achieved good results in location of a fleet [ 16 ], the selection of warships [ 17 ], and information security risk assessment in critical infrastructure [ 18 ]. Hesitant fuzzy sets (HFSs) are one of the MCDM theories, and as an extension of fuzzy sets, they have made achievements in theory as well as in numerous other fields [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Retrieval and Ranking of Combining Ontology and Content Attributes for Scientific Document

Jiang

Tian

2022

Entropy

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Traditional mathematical search models retrieve scientific documents only by mathematical expressions and their contexts and do not consider the ontological attributes of scientific documents, which result in gaps between the queries and the retrieval results. To solve this problem, a retrieval and ranking model is constructed that synthesizes the information of mathematical expressions with related texts, and the ontology attributes of scientific documents are extracted to further sort the retrieval results. First, the hesitant fuzzy set of mathematical expressions is constructed by using the characteristics of the hesitant fuzzy set to address the multi-attribute problem of mathematical expression matching; then, the similarity of the mathematical expression context sentence is calculated by using the BiLSTM two-way coding feature, and the retrieval result is obtained by synthesizing the similarity between the mathematical expression and the sentence; finally, considering the ontological attributes of scientific documents, the retrieval results are ranked to obtain the final search results. The MAP_10 value of the mathematical expression retrieval results on the Ntcir-Mathir-Wikipedia-Corpus dataset is 0.815, and the average value of the NDCG@10 of the scientific document ranking results is 0.9; these results prove the effectiveness of the scientific document retrieval and ranking method.

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“…Recently, [14] and [15] proposed the concept of basic uncertain information (BUI) which can well model and handle a large class of quantitative uncertain information including the ones aforementioned. BUI has soon been further developed and applied in several areas [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Unsymmetrical basic uncertain information with some decision-making methods

Jin

Yager

Chen

et al. 2022

IFS

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Motivated by a specific decision-making situation, this work proposes the concept and definition of unsymmetrical basic uncertain information which is a further generalization of basic uncertain information and can model uncertainties in some new decision-making situations. We show that unsymmetrical basic uncertain information in some sense can model linguistic hedges such as “at least” and “at most”. Formative weighted arithmetic means and induced aggregations are defined for the proposed concept. Rules-based decision making and semi-copula based integral for this concept with some numerical examples are also presented.

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An interval‐valued exceedance method in MCDM with uncertain satisfactions

Cited by 21 publications

References 74 publications

Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information

Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information

Retrieval and Ranking of Combining Ontology and Content Attributes for Scientific Document

Unsymmetrical basic uncertain information with some decision-making methods

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