Formalization, Prediction and Recognition of Expert Evaluations of Telemetric Data of Artificial Satellites Based on Type-II Fuzzy Sets

2019 ◽  
pp. 39-64 ◽  
Author(s):  
Olga M. Poleshchuk
Keyword(s):  
Fuzzy Sets ◽  
Artificial Satellites ◽  
Type Ii

scholarly journals Using of type-ii fuzzy sets and Z-numbers for expert group information formalization

2020 ◽  
Vol 24 (5) ◽  
pp. 116-121
Author(s):  
O.M. Poleshchuk ◽  
Keyword(s):  
Fuzzy Sets ◽  
Individual Characteristics ◽  
Type Ii ◽  
Input Information ◽  
Expert Information ◽  
Model Based ◽  
Different Types ◽  
Group Information ◽  
Semantic Spaces ◽  
The Individual

Two models of formalizing group expert information based on fuzzy sets of the second type and Z-numbers have been developed. The construction of fuzzy sets of the second type and components of Z-numbers is carried out using full orthogonal semantic spaces. The construction of semantic spaces is carried out using statistical information or information obtained as a result of a direct survey of experts. The input information for the model based on fuzzy sets of the second type are linguistic estimates of objects. The input information for the model based on Z-numbers are linguistic estimates of objects and the reliability of these estimates. The developed models expand the possibilities of processing expert information, allow preserving the individual characteristics of expert criteria embedded in the data, and at the same time correctly process different types of uncertainty inherent in this data.

A novel approach for fuzzy edge detection using type II fuzzy sets

2008 ◽  
Author(s):  
Vamsi Krishna Madasu ◽  
Madasu Hanmandlu ◽  
Shantaram Vasikarla
Keyword(s):  
Edge Detection ◽  
Fuzzy Sets ◽  
Type Ii ◽  
Novel Approach

Comment on: “Image thresholding using type II fuzzy sets”

2008 ◽  
Vol 41 (5) ◽  
pp. 1810-1811 ◽  
Author(s):  
Ioannis K. Vlachos ◽  
George D. Sergiadis
Keyword(s):  
Fuzzy Sets ◽  
Type Ii ◽  
Image Thresholding

scholarly journals Multi-Granulation Graded Rough Intuitionistic Fuzzy Sets Models Based on Dominance Relation

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 446 ◽  
Author(s):  
Zhan-ao Xue ◽  
Min-jie Lv ◽  
Dan-jie Han ◽  
Xian-wei Xin
Keyword(s):  
Information Systems ◽  
Fuzzy Sets ◽  
Rough Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Dominance Relation ◽  
Classification Error ◽  
Type I ◽  
Type Ii ◽  
Intuitionistic Fuzzy ◽  
Relation Type

From the perspective of the degrees of classification error, we proposed graded rough intuitionistic fuzzy sets as the extension of classic rough intuitionistic fuzzy sets. Firstly, combining dominance relation of graded rough sets with dominance relation in intuitionistic fuzzy ordered information systems, we designed type-I dominance relation and type-II dominance relation. Type-I dominance relation reduces the errors caused by single theory and improves the precision of ordering. Type-II dominance relation decreases the limitation of ordering by single theory. After that, we proposed graded rough intuitionistic fuzzy sets based on type-I dominance relation and type-II dominance relation. Furthermore, from the viewpoint of multi-granulation, we further established multi-granulation graded rough intuitionistic fuzzy sets models based on type-I dominance relation and type-II dominance relation. Meanwhile, some properties of these models were discussed. Finally, the validity of these models was verified by an algorithm and some relative examples.

Comment on: “Image thresholding using type II fuzzy sets”. Importance of this method

2010 ◽  
Vol 43 (9) ◽  
pp. 3188-3192 ◽  
Author(s):  
H. Bustince ◽  
E. Barrenechea ◽  
M. Pagola ◽  
J. Fernandez ◽  
J. Sanz
Keyword(s):  
Fuzzy Sets ◽  
Type Ii ◽  
Image Thresholding

Pattern recognition using type-II fuzzy sets

2005 ◽  
Vol 170 (2-4) ◽  
pp. 409-418 ◽  
Author(s):  
H MITCHELL
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Type Ii
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