An efficient centroid type-reduction strategy for general type-2 fuzzy logic system

2008 ◽  
Vol 178 (9) ◽  
pp. 2224-2236 ◽  
Author(s):  
F LIU
Keyword(s):  
Fuzzy Logic ◽  
General Type ◽  
Fuzzy Logic System ◽  
Reduction Strategy ◽  
Type Reduction ◽  
Logic System

A zSlices-based general type-2 fuzzy logic system for users-centric adaptive learning in large-scale e-learning platforms

2016 ◽  
Vol 21 (22) ◽  
pp. 6859-6880 ◽  
Author(s):  
Khalid Almohammadi ◽  
Hani Hagras ◽  
Daniyal Alghazzawi ◽  
Ghadah Aldabbagh
Keyword(s):  
Fuzzy Logic ◽  
Adaptive Learning ◽  
Large Scale ◽  
General Type ◽  
Fuzzy Logic System ◽  
E Learning ◽  
Learning Platforms ◽  
Logic System

scholarly journals Type-2 Fuzzy Logic in Pair Formation

2018 ◽  
Vol 10 (1) ◽  
pp. 94
Author(s):  
Lakshmi Shrinivasan ◽  
J. l R. Rao
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Ground Truth ◽  
Fuzzy Logic System ◽  
Pair Formation ◽  
Type Reduction ◽  
And Performance ◽  
Logic System

<span>This paper gives an overview of Type-2 Fuzzy sets (T2FSs) and Type-2 fuzzy Logic system (T2FLS) considering one aviation scenario. The existing type-1 Fuzzy system has limited capability to handle the uncertainty directly. In order to overcome the limitations of Type-1 fuzzy Logic system (T1FLS), a next level of fuzzy set is introduced, that is known as T2FSs. Here we will discuss about: Type-2 fuzzy sets, type-2 membership functions, inference engine, type reduction and defuzzification. Pair formation is the undertaken aviation scenario which is very critical in a fighting situation. Crisp data are taken by the sensors of aircraft and with the techniques of data fusion, a constant decision is passed whether two aircrafts can achieve pair formation or not. Experiments are evaluated and performance is compared with ground truth and existing T1FLS, which proves better in terms of decision making while a certain amount of uncertainty is present</span>.

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