Xiaolu Zhang

Bio: Xiaolu Zhang is an academic researcher from Jiangxi University of Finance and Economics. The author has contributed to research in topics: Pythagorean theorem & Fuzzy classification. The author has an hindex of 1, co-authored 1 publications receiving 273 citations.

A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid

Abstract: The main advances regarding the use of the Choquet and Sugeno integrals in multi-criteria decision aid over the last decade are reviewed. They concern mainly a bipolar extension of both the Choquet integral and the Sugeno integral, interesting particular submodels, new learning techniques, a better interpretation of the models and a better use of the Choquet integral in multi-criteria decision aid. Parallel to these theoretical works, the Choquet integral has been applied to many new fields, and several softwares and libraries dedicated to this model have been developed.

A Novel Approach Based on Similarity Measure for Pythagorean Fuzzy Multiple Criteria Group Decision Making

Abstract: The Pythagorean fuzzy set, as a new extension of intuitionistic fuzzy set, has recently been developed to manage the complex uncertainty in practical group decision problems. The purpose of this article is to develop a new decision method based on similarity measure to address multiple criteria group decision making problems within Pythagorean fuzzy environment based on Pythagorean fuzzy numbers PFNs. The contribution of this article is fivefold: 1 An accuracy function of PFNs is defined and a new ranking method for PFNs is proposed; 2 new Pythagorean fuzzy aggregating operators are developed; 3 a novel similarity measure for PFNs is presented, and some desirable properties are discussed; 4 a simple and effective Pythagorean fuzzy group decision method is introduced; and 5 The proposed method is applied to address the selection problem of photovoltaic cells.

Multiple-Attribute Decision-Making Based on Archimedean Bonferroni Operators of q -Rung Orthopair Fuzzy Numbers

Abstract: The theory of $q$ -rung orthopair fuzzy sets ( $q$ -ROFSs) proposed by Yager effectively describes fuzzy information in the real world. Because $q$ -ROFSs contain the parameter $q$ and can adjust the range of expressed fuzzy information, they are superior to both intuitionistic and Pythagorean fuzzy sets. Archimedean T-norm and T-conorm (ATT) is an important tool used to generate operational rules based on the q -rung orthopair fuzzy numbers ( $q$ -ROFNs). In comparison, the Bonferroni mean (BM) operator has an advantage because it considers the interrelationships between the different attributes. Therefore, it is an important and meaningful innovation to extend the BM operator to the $q$ -ROFNs based upon the ATT. In this paper, we first discuss $q$ -rung orthopair fuzzy operational rules by using ATT. Furthermore, we extend BM operator to the $q$ -ROFNs and propose the $q$ -rung orthopair fuzzy Archimedean BM $(q\hbox{-}{ROFABM})$ operator and the q -rung orthopair fuzzy weighted Archimedean BM $(q\hbox{-}{ROFWABM})$ operator and study their desirable properties. Then, a new multiple-attribute decision-making (MADM) method is developed based on $q\hbox{-}{ROFWABM}$ operator. Finally, we use a practical example to verify effectiveness and superiority by comparing to other existing methods.

Pythagorean Fuzzy Information Measures and Their Applications

Abstract: Pythagorean fuzzy set (PFS), originally proposed by Yager, is more capable than intuitionistic fuzzy set (IFS) to handle vagueness in the real world. The main purpose of this paper is to investigate the relationship between the distance measure, the similarity measure, the entropy, and the inclusion measure for PFSs. The primary goal of the study is to suggest the systematic transformation of information measures (distance measure, similarity measure, entropy, inclusion measure) for PFSs. For achieving this goal, some new formulae for information measures of PFSs are introduced. To show the efficiency of the proposed similarity measure, we apply it to pattern recognition, clustering analysis, and medical diagnosis. Some illustrative examples are given to support the findings and also demonstrate their practicality and effectiveness of similarity measure between PFSs.

Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making

Abstract: In this paper, we define the Choquet integral operator for Pythagorean fuzzy aggregation operators, such as Pythagorean fuzzy Choquet integral average PFCIA operator and Pythagorean fuzzy Choquet integral geometric PFCIG operator. The operators not only consider the importance of the elements or their ordered positions but also can reflect the correlations among the elements or their ordered positions. It is worth pointing out that most of the existing Pythagorean fuzzy aggregation operators are special cases of our operators. Meanwhile, some basic properties are discussed in detail. Later, we propose two approaches to multiple attribute group decision making with attributes involving dependent and independent by the PFCIA operator and multi-attributive border approximation area comparison MABAC in Pythagorean fuzzy environment. Finally, two illustrative examples have also been taken in the present study to verify the developed approaches and to demonstrate their practicality and effectiveness.