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Titolo
A systematic literature review of soft set theory
Autor(es)
Soggetto
Soft set
Fuzzy soft set
Soft topology
Data filling
Parameter reduction
Decision-making
Clasificación UNESCO
1102.08 Lógica Matemática
Fecha de publicación
2024-02-25
Editore
Springer
Citación
Alcantud, J.C.R., Khameneh, A.Z., Santos-García, G. y Akram, M. (2024). A systematic literature review of soft set theory. Neural Comput & Applic. https://doi.org/10.1007/s00521-024-09552-x
Resumen
[EN] Soft set theory, initially introduced through the seminal article ‘‘Soft set theory—First results’’ in 1999, has gained considerable attention in the field of mathematical modeling and decision-making. Despite its growing prominence, a comprehensive survey of soft set theory, encompassing its foundational concepts, developments, and applications, is notably absent in the existing literature. We aim to bridge this gap. This survey delves into the basic elements of the theory, including the notion of a soft set, the operations on soft sets, and their semantic interpretations. It describes various generalizations and modifications of soft set theory, such as N-soft sets, fuzzy soft sets, and bipolar soft sets, highlighting their specific characteristics. Furthermore, this work outlines the fundamentals of various extensions of mathematical structures from the perspective of soft set theory. Particularly, we present basic results of soft topology and other algebraic structures such as soft algebras and sigma-algebras. This article examines a selection of notable applications of soft set theory in different fields, including medicine and economics, underscoring its versatile nature. The survey concludes with a discussion on the challenges and future directions in soft set theory, emphasizing the need for further research to enhance its theoretical foundations and broaden its practical applications. Overall, this survey of soft set theory serves as a valuable resource for practitioners, researchers, and students interested in understanding and utilizing this flexible mathematical framework for tackling uncertainty in decision-making processes.
URI
ISSN
0941-0643
DOI
10.1007/s00521-024-09552-x
Versión del editor
Aparece en las colecciones
- BORDA. Artículos [35]