A Historical Account of Types of Fuzzy Sets and Their Relationships

In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used

The Encyclopedia of Neutrosophic Researchers - vol. 1

This is the first volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements

Research on fuzzy sets

[EN] This paper explores the advancements in soft sets and their extensions, contributing to the evolving field of soft computing. Soft sets, introduced by Molodtsov, provide a flexible framework for handling uncertainty and imprecision in decision-making processes. The research delves into various extensions of soft sets, including hybrid models with other mathematical structures, enhancing their applicability in diverse domains. Novel methodologies for parameterization and optimization within soft sets are investigated, aiming to improve their efficiency and effectiveness in real-world applications. The study emphasizes the integration of soft sets with machine learning techniques, fostering the development of intelligent systems capable of handling complex and uncertain information. The findings showcase the versatility and potential of soft sets and their extensions, opening new avenues for future research in this dynamic field