A 2-order Additive Fuzzy Measure Identification Method Based on Hesitant Fuzzy Linguistic Interaction Degree and Its Application in Credit Assessment

Nonlinear Integration ◽

Fuzzy Linguistic ◽

Context Free

Abstract In order to solve the problem that it is difficult to quantitatively evaluate the interactivity between attributes in the identification process of 2-order additive fuzzy measure, this work uses the hesitant fuzzy linguistic term set (HFLTS) to describe and deal with the interactivity between attributes. Firstly, the interactivity between attributes is defined by the supermodular game theory, and a linguistic term set is then established to characterize the interactivity between attributes. Secondly, under the linguistic term set, according to the above definition, the experts employ the linguistic expressions generated by the context-free grammar to evaluate the interactivity between attributes, and the opinions of all experts are then aggregated by using the defined hesitant fuzzy linguistic weighted power average operator (HFLWPA). Thirdly, based on the standard Euclidean distance formula of the hesitant fuzzy linguistic elements (HFLEs), the hesitant fuzzy linguistic interaction degree (HFLID) between attributes is defined and calculated by constructing a piecewise function. Finally, a 2-order additive fuzzy measure identification method based on HFLID is further proposed. Based on the proposed method, using the Choquet fuzzy integral as nonlinear integration operator, a multi-attribute decision making (MADM) process is presented. Taking the credit assessment of the big data listed companies in China as an application example, the feasibility and effectiveness of the proposed method is verified by the analysis results of application example.

A 2-order additive fuzzy measure identification method based on intuitionistic fuzzy sets and its application in credit evaluation

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201368 ◽

2021 ◽

pp. 1-13

Author(s):

Mu Zhang ◽

Si-si Li ◽

Bi-bin Zhao

Keyword(s):

Fuzzy Sets ◽

Weighted Average ◽

Score Function ◽

Intuitionistic Fuzzy Sets ◽

Fuzzy Measure ◽

Credit Evaluation ◽

Supermodular Game ◽

Identification Method ◽

Intuitionistic Fuzzy ◽

Multi Attribute Decision Making

In view of the problem that it is difficult to quantitatively assess the interactivity between attributes in the identification process of 2-order additive fuzzy measure, this work uses the intuitionistic fuzzy sets (IFSs) to describe and deal with the interactivity between attributes. Firstly, the interactivity between attributes is defined by the supermodular game theory. On this basis, the experts employ the intuitionistic fuzzy number (IFN) to assess the interactivity between attributes, Secondly, the opinions of all experts are aggregated by using the intuitionistic fuzzy weighted average operator (IFWA). Finally, based on the aggregated results, the intuitionistic fuzzy interaction degree between attributes is defined and calculated by the score function of IFN. Thus, a 2-order additive fuzzy measure identification method based on IFSs is further proposed. Based on the proposed method, using the Choquet fuzzy integral as nonlinear integration operator, a multi-attribute decision making (MADM) process is presented. Taking the credit evaluation of the big data listed companies in China as an application example, the feasibility and effectiveness of the proposed method is verified by the analysis results of application example.

A Novel Multi-Attribute Decision Making Method Based on The Double Hierarchy Hesitant Fuzzy Linguistic Generalized Power Aggregation Operator

Information ◽

10.3390/info10110339 ◽

2019 ◽

Vol 10 (11) ◽

pp. 339 ◽

Cited By ~ 4

Author(s):

Liu ◽

Zhao ◽

Li ◽

Wang ◽

Wang

Keyword(s):

Decision Making ◽

Aggregation Operators ◽

Linguistic Context ◽

Practical Application ◽

Linguistic Expression ◽

Novel Approach ◽

Linguistic Term ◽

Complex Decision ◽

. A double hierarchy hesitant fuzzy linguistic term set (DHHFLT) is deemed as an effective and powerful linguistic expression which models complex linguistic decision information more accurately by using two different hierarchy linguistic term sets. The purpose of this paper is to propose a multi-attribute decision making method to tackle complex decision issues in which attribute values are represented as double hierarchy hesitant fuzzy linguistic numbers, and there are some extreme or unreasonable data in the attribute values. To do this, firstly, four double hierarchy hesitant fuzzy linguistic generalized power aggregation operators are introduced, including the double hierarchy hesitant fuzzy linguistic generalized power average (DHHFLGPA) operator, the double hierarchy hesitant fuzzy linguistic generalized power geometric (DHHFLGPG) operator, and their weighted forms. Thereafter, several favorable properties, as well as representative cases of the proposed operators, are investigated in detail. Moreover, by virtue of the proposed operators, a novel approach is developed for coping with multi-attribute decision making cases in the double hierarchy hesitant fuzzy linguistic context. Finally, an illustrated example is given to demonstrate the practical application of the presented approach, an availability verification is given to show its validity, and a comparative analysis is also conducted to highlight the advantages of the proposed approach.

AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488500000381 ◽

2000 ◽

Vol 08 (05) ◽

pp. 539-562 ◽

Cited By ~ 258

Author(s):

F. HERRERA ◽

L. MARTINEZ

Keyword(s):

Decision Making ◽

Linguistic Information ◽

Loss Of Information ◽

Linguistic Representation ◽

Representation Model ◽

Decision Making Problem ◽

Linguistic Term ◽

Fuzzy Linguistic ◽

Transformation Processes

In this paper we shall develop a procedure for combining numerical and linguistic information without loss of information in the transformation processes between numerical and linguistic information, taking as base for representing the information the 2-tuple fuzzy linguistic representation model. We shall analyze the conditions to impose the linguistic term set in order to ensure that the combination procedure does not produce any loss of information. Afterwards the aggregation process will be applied to a decision procedure over a multi-attribute decision-making problem dealing with numerical and linguistic information, that is, with qualitative and quantitative attributes.

A Novel Group Decision-Making Approach for Hesitant Fuzzy Linguistic Term Sets and Its Application to VIKOR

Mathematical Problems in Engineering ◽

10.1155/2020/7682983 ◽

2020 ◽

Vol 2020 ◽

pp. 1-20

Author(s):

Xiuli Geng ◽

Yunting Jin ◽

Yongzheng Zhang

Keyword(s):

Decision Making ◽

Rough Set ◽

Group Decision Making ◽

Rough Set Theory ◽

Group Decision ◽

Vikor Method ◽

Context Free Grammar ◽

Linguistic Term ◽

Fuzzy Linguistic ◽

Context Free

This paper develops a novel group decision-making (GDM) approach for solving multiple-criteria group decision-making (MCGDM) problems with uncertainty. The hesitant fuzzy linguistic term sets (HFLTSs) are applied to elicit the decision makers’ linguistic preferences due to their distinguished efficiency and flexibility in representing uncertainty. However, the existing context-free grammar for linguistic description cannot allow generating the linguistic expressions completely free to limit the richness of HFLTSs, and the related methods for dealing with HFLTSs also have limitations in aggregating HFLTSs with different lengths and types. Therefore, this paper proposes extended context-free grammar and a novel GDM approach for HFLTSs, considering the advantages of the rough set theory and OWA operators. The rough set theory can manage the uncertainty existing in the fuzzy representation and deal with HFLTSs represented by the 2-tuple fuzzy linguistic model to get rough number sets. The OWA operator can aggregate these sets with different numbers of elements into an interval simply and objectively. Then, an extended VIKOR method based on the proposed GDM approach for HFLTSs is presented to solve the MCGDM problems. Finally, two examples are given to illustrate the applicability and validity of the developed GDM approach and the hesitant VIKOR method through sensitivity and comparison analysis with other existing approaches.

Group Decision Making Method Based on Composite Linguistic Expressions

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1049-1050.1281 ◽

2014 ◽

Vol 1049-1050 ◽

pp. 1281-1286

Author(s):

Wen Zhan Dai ◽

Yun Li

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Linguistic Terms ◽

Traditional Use ◽

Linguistic Term ◽

The One ◽

Decision Making Model ◽

Fuzzy Linguistic ◽

Context Free

When decision makers are hesitant among different linguistic terms, the traditional use of one single linguistic term will restrict the accuracy of personal preference expressed by experts, it is necessary to use composite linguistic term which contains both the one single linguistic terms and the comparative linguistic expressions. Firstly, with the use of context-free grammars, two-tuple linguistic representation model and hesitant fuzzy linguistic term sets, the linguistic expressions of the preference relations provided by experts are transformed into judgment matrix, then the suitable aggregation operators will be selected to obtain a best solution to the problem. Finally, a new group decision making model based on composite linguistic expressions has been proposed and a practical example has been analyzed to verify the reasonability and feasibility of the approach.

Two-sided matching decision making with multi-granular hesitant fuzzy linguistic term sets and incomplete criteria weight information

Expert Systems with Applications ◽

10.1016/j.eswa.2020.114311 ◽

2020 ◽

pp. 114311

Author(s):

Zhen Zhang ◽

Junliang Gao ◽

Yuan Gao ◽

Wenyu Yu

Keyword(s):

Decision Making ◽

Linguistic Term ◽

A multi-attribute decision-making framework for Chinese Medicine medical diagnosis with correlation measures under double hierarchy hesitant fuzzy linguistic environment

Computers & Industrial Engineering ◽

10.1016/j.cie.2021.107243 ◽

2021 ◽

pp. 107243

Author(s):

Ruichen Zhang ◽

Xunjie Gou ◽

Zeshui Xu

Keyword(s):

Decision Making ◽

Chinese Medicine ◽

Medical Diagnosis ◽

Correlation Measures ◽

Decision Making Framework ◽

Hesitant Fuzzy Linguistic Agglomerative Hierarchical Clustering Algorithm and Its Application in Judicial Practice

Mathematics ◽

10.3390/math9040370 ◽

2021 ◽

Vol 9 (4) ◽

pp. 370

Author(s):

Shuangsheng Wu ◽

Jie Lin ◽

Zhenyu Zhang ◽

Yushu Yang

Keyword(s):

Hierarchical Clustering ◽

Clustering Algorithm ◽

Clustering Algorithms ◽

Agglomerative Hierarchical Clustering ◽

Research Gaps ◽

Judicial Practice ◽

Linguistic Term ◽

Clustering Effect ◽

Hierarchical Clustering Algorithm ◽

The fuzzy clustering algorithm has become a research hotspot in many fields because of its better clustering effect and data expression ability. However, little research focuses on the clustering of hesitant fuzzy linguistic term sets (HFLTSs). To fill in the research gaps, we extend the data type of clustering to hesitant fuzzy linguistic information. A kind of hesitant fuzzy linguistic agglomerative hierarchical clustering algorithm is proposed. Furthermore, we propose a hesitant fuzzy linguistic Boole matrix clustering algorithm and compare the two clustering algorithms. The proposed clustering algorithms are applied in the field of judicial execution, which provides decision support for the executive judge to determine the focus of the investigation and the control. A clustering example verifies the clustering algorithm’s effectiveness in the context of hesitant fuzzy linguistic decision information.