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Symmetry
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Probabilistic Preference Theory and Applications in Complexity and Symmetry System...
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Probabilistic Preference Theory and Applications in Complexity and Symmetry System Modeling

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 3723

Special Issue Editors

Prof. Dr. Zeshui Xu

E-Mail Website
Guest Editor
Business School, Sichuan University, Chengdu 610064, China
Interests: decision making; fuzzy sets; bibliometrics
Prof. Dr. Wei Zhou

E-Mail Website
Guest Editor
Business School, Yunnan University of Finance and Economics, Kunming 650221, China
Interests: risk decision making; fuzzy sets; information fusion
Prof. Dr. Decui Liang

E-Mail Website
Guest Editor
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
Interests: decision analysis based on big data; information management and business intelligence; risk evaluation and management
Special Issues, Collections and Topics in MDPI journals
Dr. Hai Wang

E-Mail Website
Guest Editor
School of Information Engineering, Nanjing Audit University, Nanjing, Jiangsu 211815, China
Interests: decision making; fuzzy sets

Special Issue Information

Dear Colleagues,

Given the amount of information processing required to study complexity, the use of computers and mathematical tools has been central to complex systems research. Probabilistic preference theory, including probabilistic-based expressions, refers to a conceptual framework using probabilities to align humans’ thoughts and perceptions. As a broadly researched notion, symmetry also reflects specific characteristics, property, and evolutionary trends from simple data to model calculations, which could help people dealing with complexities and uncertainties in real life.

This Special Issue aims to emphasize the applications of probabilistic preference theory and its applications in complexity and symmetry system modeling, which would be of great significance to expand new theoretical directions and practical applications.

We invite researchers and experts worldwide to submit high-quality original research papers that focus on probabilistic preference theory, complexity, and symmetry systems, especially including the following topics:

⋆ Probabilistic linguistic term set and symmetry system modeling;

⋆ Probabilistic hesitant fuzzy set and symmetry system modeling;

⋆ Symmetry system modeling with probabilistic preference sets;

⋆ Complexity system modeling with probabilistic preference sets;

⋆ Applications in big data analytics of symmetry systems;

⋆ Applications in modern AI of probabilistic preference theory.

Prof. Dr. Zeshui Xu
Prof. Dr. Wei Zhou
Prof. Dr. Decui Liang
Dr. Hai Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • probabilistic preference
  • probabilistic linguistic term set
  • probabilistic hesitant fuzzy set
  • complexity system
  • symmetry system
  • modeling

Published Papers (2 papers)

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Research

25 pages, 423 KiB  
Article
Temporal Behavior of Local Characteristics in Complex Networks with Preferential Attachment-Based Growth
by Sergei Sidorov, Sergei Mironov, Nina Agafonova and Dmitry Kadomtsev
Symmetry 2021, 13(9), 1567; https://doi.org/10.3390/sym13091567 - 25 Aug 2021
Cited by 3 | Viewed by 1346
Abstract
The study of temporal behavior of local characteristics in complex growing networks makes it possible to more accurately understand the processes caused by the development of interconnections and links between parts of the complex system that occur as a result of its growth. [...] Read more.
The study of temporal behavior of local characteristics in complex growing networks makes it possible to more accurately understand the processes caused by the development of interconnections and links between parts of the complex system that occur as a result of its growth. The spatial position of an element of the system, determined on the basis of connections with its other elements, is constantly changing as the result of these dynamic processes. In this paper, we examine two non-stationary Markov stochastic processes related to the evolution of Barabási–Albert networks: the first describes the dynamics of the degree of a fixed node in the network, and the second is related to the dynamics of the total degree of its neighbors. We evaluate the temporal behavior of some characteristics of the distributions of these two random variables, which are associated with higher-order moments, including their variation, skewness, and kurtosis. The analysis shows that both distributions have a variation coefficient close to 1, positive skewness, and a kurtosis greater than 3. This means that both distributions have huge standard deviations that are of the same order of magnitude as the expected values. Moreover, they are asymmetric with fat right-hand tails. Full article
(This article belongs to the Special Issue Probabilistic Preference Theory and Applications in Complexity and Symmetry System Modeling)
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18 pages, 326 KiB  
Article
Three-Way Multi-Attribute Decision Making Based on Outranking Relations under Intuitionistic Fuzzy Environments
by Zengtai Gong and Le Fan
Symmetry 2021, 13(8), 1384; https://doi.org/10.3390/sym13081384 - 29 Jul 2021
Cited by 3 | Viewed by 1493
Abstract
With the increasing complexity of the human social environment, it is impossible to describe each object in detail with accurate numbers when solving multiple attribute decision-making (MADM) problems. Compared with the fuzzy set (FS), the intuitionistic fuzzy set (IFS) not only has obvious [...] Read more.
With the increasing complexity of the human social environment, it is impossible to describe each object in detail with accurate numbers when solving multiple attribute decision-making (MADM) problems. Compared with the fuzzy set (FS), the intuitionistic fuzzy set (IFS) not only has obvious advantages in allocating ambiguous values to the object to be considered, but also takes into account the degree of membership and non-membership, so it is more suitable for decision makers (DMs) to deal with complex realistic problems. Therefore, it is of great significance to propose a MADM method under an intuitionistic fuzzy environment. Moreover, compared with the traditional 2WD, by putting forward the option of delay, the decision-making risk can be effectively reduced using three-way decision (3WD). In addition, the binary relations between objects in the decision-making process have been continuously generalized, such as equivalence relation which have symmetrical relationship, dominance relation and outranking relation, which are worthy of study. In this paper, we propose 3WD-MADM method based on IF environment and the objective IFS is calculated by using the information table. Then, the hybrid information table is used to solve the supplier selection problem to demonstrate the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Probabilistic Preference Theory and Applications in Complexity and Symmetry System Modeling)
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