Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Multi-granulation double fuzzy rough sets
View through CrossRef
Based on the definition of double fuzzy relations, two types of new rough set models are constructed, which are multi-granulation double fuzzy rough sets called optimistic and pessimistic multi-granulation double fuzzy rough sets, and some of their properties were studied. In addition, we study the relationship between optimistic and pessimistic multi-granulation double fuzzy rough sets and double fuzzy rough sets.
Title: Multi-granulation double fuzzy rough sets
Description:
Based on the definition of double fuzzy relations, two types of new rough set models are constructed, which are multi-granulation double fuzzy rough sets called optimistic and pessimistic multi-granulation double fuzzy rough sets, and some of their properties were studied.
In addition, we study the relationship between optimistic and pessimistic multi-granulation double fuzzy rough sets and double fuzzy rough sets.
Related Results
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
New Approaches of Generalised Fuzzy Soft sets on fuzzy Codes and Its Properties on Decision-Makings
Background Several scholars defined the concepts of fuzzy soft set theory and their application on decision-making problem. Based on this concept, researchers defined the generalis...
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Konstruksi Sistem Inferensi Fuzzy Menggunakan Subtractive Fuzzy C-Means pada Data Parkinson
Abstract. Fuzzy Inference System requires several stages to get the output, 1) formation of fuzzy sets, 2) formation of rules, 3) application of implication functions, 4) compositi...
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Generated Fuzzy Quasi-ideals in Ternary Semigroups
Here in this paper, we provide characterizations of fuzzy quasi-ideal in terms of level and strong level subsets. Along with it, we provide expression for the generated fuzzy quasi...
Characterized Fuzzy R2.5 and Characterized Fuzzy T3.5 Spaces
Characterized Fuzzy R2.5 and Characterized Fuzzy T3.5 Spaces
This paper, deals with, introduce and study the notions of haracterized fuzzy R2.5 spaces and of characterized fuzzy T3.5 spaces by using the notion of fuzzy function family presen...
FUZRUF-onto: a Methodology to Develop Fuzzy Rough Ontologies
FUZRUF-onto: a Methodology to Develop Fuzzy Rough Ontologies
Abstract
Nowadays, semantic web technologies play a crucial role in knowledge representation paradigm. With the raise of imprecise and vague knowledge, there is an upsurge ...
ω – SUBSEMIRING FUZZY
ω – SUBSEMIRING FUZZY
Mapping ρ is called a fuzzy subset of an empty set of S if ρ is the mapping from S to the closed interval [0,1]. A fuzzy subset ρ introduced into this paper is a fuzzy subset of se...
FUZZY‐FUZZY AUTOMATA
FUZZY‐FUZZY AUTOMATA
Based on the concept of fuzzy sets of type 2 (or fuzzy‐fuzzy sets) defined by L. A. Zadeh, fuzzy‐fuzzy automata ate newly formulated and some properties of these automata are inves...