Results 21 to 30 of about 3,651 (294)
A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration [PDF]
, 2016 Considering the need for more effective decision support in the context of distributed manufacturing, this paper develops an advanced analytics framework for configuring supply chain (SC) networks.
Shukla, Nagesh, Kiridena, Senevi
core +4 more sources
Journal of Mathematics, 2021 Multigranulation rough set theory is an important tool to deal with the problem of multicriteria information system. The notion of fuzzy β-neighborhood has been used to construct some covering-based multigranulation fuzzy rough set (CMFRS) models through
Zaibin Chang, Lingling Mao
doaj +1 more source
Soft rough fuzzy sets and soft fuzzy rough sets
Computers & Mathematics with Applications, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dan Meng, Xiaohong Zhang 0001, Keyun Qin
openaire +1 more source
Similarity Measure: An Intuitionistic Fuzzy Rough Set Approach [PDF]
Transactions on Fuzzy Sets and Systems, 2023 In fuzzy set theory, the concept of a non-membership function and the hesitation margin were not considered while these two concepts have been included along with the membership function for intuitionistic fuzzy sets. It is also to be noted that the
Jaydip Bhattacharya
doaj +1 more source
On the lattice of fuzzy rough sets [PDF]
, 2023 By the means of lower and upper fuzzy approximations we define quasiorders. Their properties are used to prove our main results. First, we characterize those pairs of fuzzy sets which form fuzzy rough sets w.r.t.
Radeleczki, Sándor, Gégény, Dávid
core
Intuitionistic Fuzzy Soft Rough Set and Its Application in Decision Making
Abstract and Applied Analysis, 2014 The soft set theory, originally proposed by Molodtsov, can be used as a general mathematical tool for dealing with uncertainty. In this paper, we present concepts of soft rough intuitionistic fuzzy sets and intuitionistic fuzzy soft rough sets, and ...
Haidong Zhang, Lan Shu, Shilong Liao
doaj +1 more source
Complex & Intelligent Systems, 2023 Fuzzy rough set models are useful tools for dealing with fuzzy and real-valued data. They have been used in many real-world applications. In this paper, we investigate the fuzzy rough set model based on triangular norms and fuzzy implications.
Zhaohao Wang
doaj +1 more source
Uncertainty Measure for Multisource Intuitionistic Fuzzy Information System
Complexity, 2022 Multisource information systems and multigranulation intuitionistic fuzzy rough sets are important extended types of Pawlak’s classical rough set model.
Hong Wang, Hong Li
doaj +1 more source
Rough semigroups and rough fuzzy semigroups based on fuzzy ideals
Open Mathematics, 2016 In this paper, we firstly introduce a special congruence relation U(μ, t) induced by a fuzzy ideal μ in a semigroup S. Then we define the lower and upper approximations based on a fuzzy ideal in semigroups. We can establish rough semigroups, rough ideals,
Wang Qiumei, Zhan Jianming
doaj +1 more source
Rough Standard Neutrosophic Sets: An Application on Standard Neutrosophic Information Systems [PDF]
Neutrosophic Sets and Systems, 2016 A rough fuzzy set is the result of the approximation of a fuzzy set with respect to a crisp approximation space. It is a mathematical tool for the knowledge discovery in the fuzzy information systems.
Nguyen Xuan Thao +2 more
doaj +1 more source