An Intuitionistic Fuzzy Set Based Approach to Intelligent Data Analysis: An Application to Medical Diagnosis

2003 ◽  
pp. 57-70 ◽  
Author(s):  
Eulalia Szmidt ◽  
Janusz Kacprzyk
Keyword(s):  
Data Analysis ◽  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Intelligent Data Analysis ◽  
Intuitionistic Fuzzy

Medical diagnosis using intuitionistic fuzzy set in terms shortest distance measure

2018 ◽  
Vol 11 (3) ◽  
pp. 949 ◽  
Author(s):  
G. Deepa ◽  
B. Praba ◽  
A. Manimaran ◽  
V.M. Chandrasekaran ◽  
K. Rajakumar
Keyword(s):  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Distance Measure ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy ◽  
Shortest Distance

scholarly journals Diagnosis of Vector-Borne Diseases Using MCDM Techniques

2019 ◽  
Vol 8 (6) ◽  
pp. 1367-1375
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Diagnostic Tool ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Vector Borne Diseases ◽  
Intuitionistic Fuzzy ◽  
The World ◽  
Vector Borne ◽  
Vikor Technique

Vector -borne diseases (VBDs) are one of the major problems of human are affecting adversely to people each year in every part of the world. In this work multiple decision-making technique is used to provide a better diagnosis for VBDs. It evaluates alternative diseases having contradictory symptoms. It is very tough to exactly determine crsiteria weight as well as rating of alternatives (diseases) on each criterion. Here VIKOR approach is applied for medical diagnosis of VBDs such as malaria, chikungunya, and dengue, and also used the notion of intuitionistic fuzzy set (IFS) theory to explain this concept. Furthermore, criteria selected according to relevant disease and weights assigned to them by medical experts. In order to accomplish the objective, patients’ data has been acquired using a questionnaire from three medical experts of Delhi region. The study shows that final outcomes are same as diagnosed by doctors regarding actual diseases as that by employing VIKOR technique based on questionnaire information. Thus, MCDM methodology can help in correct and timely diagnosis of VBDs and provides doctors a scientific diagnostic tool.

scholarly journals An Improved Correlation Coefficient of Intuitionistic Fuzzy Sets

2019 ◽  
Vol 28 (2) ◽  
pp. 231-243 ◽  
Author(s):  
Han-Liang Huang ◽  
Yuting Guo
Keyword(s):  
Fuzzy Sets ◽  
Correlation Coefficient ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
Interval Valued

Abstract The intuitionistic fuzzy set is a useful tool to deal with vagueness and uncertainty. Correlation coefficient of the intuitionistic fuzzy sets is an important measure in intuitionistic fuzzy set theory and has great practical potential in a variety of areas, such as decision making, medical diagnosis, pattern recognition, etc. In this paper, an improved correlation coefficient of the intuitionistic fuzzy sets is defined, and it can overcome some drawbacks of the existing ones. The properties of this correlation coefficient are discussed. Then, the generalization of the coefficient of interval-valued intuitionistic fuzzy sets is also introduced. Finally, two examples about the application of the proposed correlation coefficient of the intuitionistic fuzzy sets in medical diagnosis and clustering are shown to illustrate the advantages over the existing methods.

scholarly journals New Similarity Measure between Intuitionistic Fuzzy Multisets based on Tangent Function and its Application in Medical Diagnosis

2019 ◽  
Vol 8 (2S3) ◽  
pp. 161-165 ◽  
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Similarity Measure ◽  
Fuzzy Set ◽  
Medical Diagnosis ◽  
Intuitionistic Fuzzy Set ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy ◽  
Tangent Function

In recent years, Intuitionistic fuzzy set is very useful in decision making problems such as medical diagnosis, pattern recognition, clustering etc., which deals with vagueness and uncertainty. Similarity measure is a tool used to find the closeness of the intuitionistic fuzzy sets by considering the membership, nonmembership and hesitation function. In this paper, we propose an effective similarity measure based on tangent function for intuitionistic fuzzy multi sets in which membership, nonmembership, hesitation function occurs more than once and also we apply this measure in medical diagnosis and pattern recognition.

The prediction of online time series with concept drift based on dynamic intuitionistic fuzzy cognitive map

2021 ◽  
Vol 25 (4) ◽  
pp. 949-972
Author(s):  
Nannan Zhang ◽  
Xixi Yao ◽  
Chao Luo
Keyword(s):  
Fuzzy Set ◽  
Sequence Data ◽  
Concept Drift ◽  
Intuitionistic Fuzzy Set ◽  
Cognitive Map ◽  
Fuzzy Cognitive Maps ◽  
Fuzzy Cognitive Map ◽  
Online Data ◽  
Intuitionistic Fuzzy ◽  
Public Data

Fuzzy cognitive maps (FCMs) have widely been applied for knowledge representation and reasoning. However, in real life, reasoning is always accompanied with hesitation, which is deriving from the uncertainty and fuzziness. Especially, when processing the online data, since the internal and external interference, the distribution and characteristics of sequence data would be considerably changed along with the passage of time, which further increase the difficulty of modeling. In this article, based on intuitionistic fuzzy set theory, a new dynamic intuitionistic fuzzy cognitive map (DIFCM) scheme is proposed for online data prediction. Combined with a novel detection algorithm of concept drift, the structure of DIFCM can be adaptively updated with the online learning scheme, which can effectively improve the representation of online information by capturing the real-time changes of sequence data. Moreover, in order to tackle with the possible hesitancy in the process of modeling, intuitionistic fuzzy set is applied in the construction of dynamic FCM, where hesitation degree as a quantitative index explicitly expresses the hesitancy. Finally, a series of experiments using public data sets verify the effectiveness of the proposed method.

Complex intuitionistic fuzzy Maclaurin symmetric mean operators and its application to emergency program selection

2021 ◽  
pp. 1-22
Author(s):  
Riaz Ali ◽  
Saleem Abdullah ◽  
Shakoor Muhammad ◽  
Muhammad Naeem ◽  
Ronnason Chinram
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Intuitionistic Fuzzy Set ◽  
Score Functions ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Program Selection ◽  
Maclaurin Symmetric Mean ◽  
Complex Intuitionistic Fuzzy Set

Due to the indeterminacy and uncertainty of the decision-makers (DM) in the complex decision making problems of daily life, evaluation and aggregation of the information usually becomes a complicated task. In literature many theories and fuzzy sets (FS) are presented for the evaluation of these decision tasks, but most of these theories and fuzzy sets have failed to explain the uncertainty and vagueness in the decision making issues. Therefore, we use complex intuitionistic fuzzy set (CIFS) instead of fuzzy set and intuitionistic fuzzy set (IFS). A new type of aggregation operation is also developed by the use of complex intuitionistic fuzzy numbers (CIFNs), their accuracy and the score functions are also discussed in detail. Moreover, we utilized the Maclaurin symmetric mean (MSM) operator, which have the ability to capture the relationship among multi-input arguments, as a result, CIF Maclarurin symmetric mean (CIFMSM) operator and CIF dual Maclaurin symmetric mean (CIFDMSM) operator are presented and their characteristics are discussed in detail. On the basis of these operators, a MAGDM method is presented for the solution of group decision making problems. Finally, the validation of the propounded approach is proved by evaluating a numerical example, and by the comparison with the previously researched results.

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