Results 11 to 20 of about 295,676 (258)
Decomposition of Fuzzy Soft Sets with Finite Value Spaces [PDF]
The Scientific World Journal, 2014 The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty.
Feng Feng +3 more
doaj +8 more sources
New generalization of fuzzy soft sets: $ (a, b) $-Fuzzy soft sets
AIMS Mathematics, 2023 Many models of uncertain knowledge have been designed that combine expanded views of fuzziness (expressions of partial memberships) with parameterization (multiple subsethood indexed by a parameter set).
Tareq M. Al-shami +2 more
doaj +3 more sources
Fuzzy Soft Sets and Fuzzy Soft Lattices [PDF]
International Journal of Computational Intelligence Systems, 2012 The theory of soft sets was introduced by Molodtsov in 1999 in order to deal with uncertainties. In this paper, the notion of fuzzy soft lattice is defined and some related properties are derived, which extends the notion of a fuzzy lattice to include ...
Yingchao Shao, Keyun Qin
doaj +5 more sources
On Some Nonclassical Algebraic Properties of Interval-Valued Fuzzy Soft Sets [PDF]
The Scientific World Journal, 2014 Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov’s soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets.
Xiaoyan Liu, Feng Feng, Hui Zhang
doaj +4 more sources
Advances in Fuzzy Systems, 2009 We further contribute to the properties of fuzzy soft sets as defined and studied in the work of Maji et al. ( 2001), Roy and Maji (2007), and Yang et al. (2007) and support them with examples and counterexamples. We improve Proposition 3.3 by Maji et al.
B. Ahmad, Athar Kharal
doaj +4 more sources
Similarity measure and entropy of fuzzy soft sets. [PDF]
ScientificWorldJournal, 2014 Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. Recently, uncertainty measures of soft sets and fuzzy soft sets have gained attentions from researchers. This paper is devoted to the study of uncertainty measures of fuzzy soft sets.
Liu Z, Qin K, Pei Z.
europepmc +8 more sources
On Topological Structures of Fuzzy Parametrized Soft Sets [PDF]
The Scientific World Journal, 2014 We introduce the topological structure of fuzzy parametrized soft sets and fuzzy parametrized soft mappings. We define the notion of quasi-coincidence for fuzzy parametrized soft sets and investigated its basic properties. We study the closure, interior,
Serkan Atmaca, İdris Zorlutuna
doaj +12 more sources
New aggregation operators on group-based generalized intuitionistic fuzzy soft sets [PDF]
Soft comput, 2021 The approach of dealing with uncertainty is enhancing day-by-day with new rudiments and tools which possess their specific qualities. Usually, aggregation operators can easily manage the information in an exact manner.
K. Hayat +3 more
semanticscholar +2 more sources
The novel VIKOR methods for generalized Pythagorean fuzzy soft sets and its application to children of early childhood in COVID-19 quarantine [PDF]
Neural Comput Appl, 2021 In this work, the new VIKOR methods are established using the generalized Pythagorean fuzzy soft sets (GPFSSs). For GPFSSs, the distance measures such as Hamming, Euclidean, and generalized are given.
M. Kirişci +4 more
semanticscholar +2 more sources
Intertemporal Choice of Fuzzy Soft Sets [PDF]
Symmetry, 2018 This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade.
José Carlos R. Alcantud +1 more
openaire +8 more sources