GENERALIZED FUZZY DIVERGENCE MEASURE, PATTERN RECOGNITION AND INEQUALITIES

Many fuzzy information and divergence measures developed by various researchers and authors. Here, authors proposed new fuzzy divergence measure using the properties of convex function and fuzzy concept. The applications of novel fuzzy divergence measures in pattern recognition with case study, are discussed. Obtained various novel fuzzy information inequalities on fuzzy divergence measures. The new relations among new and existing fuzzy divergence measure by new f-divergence, Jensen inequalities, properties of convex functions and inequalities have studied. Finally, verified these results and proposed fuzzy divergence measures by numerical example.

Measures of Populism in the CHES 2017 Dataset

Populism is a fuzzy concept in world politics; it can take many shapes and colors, thus evading rigorous definition. Using expert evaluations provided in Chapel Hill Expert Survey (CHES) 2017 data, we try to identify features that predict populism and to characterize various European parties on a populism scale. As a byproduct, we find that experts have often diverging opinions on a party’s stance on various issues. Keywords: populism, CHES 2017, EU politics

Matrix-based reduction approach for one-sided fuzzy three-way concept lattices

Three-way concept analysis is a mathematical model of the combination of formal concept analysis and three-way decision, and knowledge discovery plays a significant impact on formal fuzzy contexts since such datasets are frequently encountered in real life. In this paper, a novel type of one-sided fuzzy three-way concept lattices is presented in a given formal fuzzy context with its complement, in which a ternary classification is available. In such case, we comprehensively explore the connections between the proposed models and classical fuzzy concept lattices among elements, sets, and orders. Furthermore, approaches to granular matrix-based reductions are investigated, by which granular consistent sets, and granular reducts via discernibility Boolean matrices are tectonically put forward. At last, the demonstrated results are performed by several experiments which enrich the research of three-way concept analysis.

Defining Public Interest in Planning: A Review

Public interest as the main content and purpose of planning is a fuzzy concept in planning literature. The body of literature on the public interest is so complex and diverse that makes it difficult to define and use the concept. In this study, the various definitions are categorized to achieve a framework of the definition of public interest. In addition to being more comprehensive than previous studies, this categorization identifies the main dimensions of a comprehensive definition of public interest. It provides a suitable context for theorists and professionals to have a clear framework for defining the public interest.

Gradation of Fuzzy Preconcept Lattices

Noticing certain limitations of concept lattices in the fuzzy context, especially in view of their practical applications, in this paper, we propose a more general approach based on what we call graded fuzzy preconcept lattices. We believe that this approach is more adequate for dealing with fuzzy information then the one based on fuzzy concept lattices. We consider two possible gradation methods of fuzzy preconcept lattice—an inner one, called D-gradation and an outer one, called M-gradation, study their properties, and illustrate by a series of examples, in particular, of practical nature.

What is the Septuagint?

In standard English usage the term Septuagint typically denotes the earliest Greek version of the Old Testament. Despite this seeming clarity, it is in fact a fuzzy concept, insofar as the boundaries of its application shift significantly from one context to another. This chapter delineates the four principal ways in which the term is currently used by biblical scholars, and discusses the historical background of each with reference to the reception of the Jewish Greek Scriptures. It begins with their inception in Hellenistic Judaism, and traces their reconfiguration by early Jewish and Christian tradents through to the advent of modernity and the rise of critical scholarship. Current issues in the field of Septuagint Studies are addressed.

Single-valued Plithogenic graph for handling multi-valued attribute data and its context

Recently, several researchers paid attention to dealing with uncertainty in data with neutrosophic attributes. In this process, a problem is addressed while dealing with contradiction and its impact on decision-making. It is considered as one of the major issues for data science researchers working in a three-way fuzzy concept lattice. To deal with this issue, the current paper tried to introduce the algebra of a single-valued Plithogenic graph and its visualization based on infimum and supremum. The proposed method is also demonstrated with an illustrative example for better understanding.

The Concept of Solidarity

Solidarity is a fuzzy concept although it is a core concept of the EU historically. Aline Bartenstein's book contributes to the clarification and analysis of the concept of solidarity between EU member states. In the theoretical part, she develops a novel conceptual approach to studying solidarity that goes beyond it having a purely political declarative function and is able to capture the dynamic of solidarity as a legal norm. In the empirical part, the author applies the concept to the integration processes in the natural gas sector between 2002 and 2019. Her analysis shows that an institutionalised principle of solidarity is in the making in the EU.

Reasoning on vague ontologies using rough set theory

Web ontologies can contain vague concepts, which means the knowledge about them is imprecise and then query answering will not possible due to the open world assumption. A concept description can be very exact (crisp concept) or exact (fuzzy concept) if its knowledge is complete, otherwise it is inexact (vague concept) if its knowledge is incomplete. In this paper, we propose a method based on the rough set theory for reasoning on vague ontologies. With this method, the detection of vague concepts will insert into the original ontology new rough vague concepts where their description is defined on approximation spaces to be used by extended Tableau algorithm for automatic reasoning. The extended Tableau algorithm by this rough set-based vagueness is intended to answer queries even with the presence of incomplete information.