<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this study, in order to prevent information loss, we propose two dissimilarity measures between intuitionistic fuzzy sets (<italic>IFSs</italic>), which consider membership and non-membership degree and <italic>IFSs</italic> is farther extension of Fuzzy sets (<italic>FSs</italic>). Additionally, we have examined the characteristics of the proposed metrics to confirm their validity. We then conducted a series of experiments, including numerical experimentation, pattern recognition, and clustering analysis, to evaluate the efficacy of these metrics. The comparative outcomes illustrate that our dissimilarity metrics are more straightforward, easy to understand, and superior to the majority of the existing methods.</p>
</abstract>

In this study, in order to prevent information loss, we propose two dissimilarity measures between intuitionistic fuzzy sets (IFSs), which consider membership and non-membership degree and IFSs is farther extension of Fuzzy sets (FSs). Additionally, we have examined the characteristics of the proposed metrics to confirm their validity. We then conducted a series of experiments, including numerical experimentation, pattern recognition, and clustering analysis, to evaluate the efficacy of these metrics. The comparative outcomes illustrate that our dissimilarity metrics are more straightforward, easy to understand, and superior to the majority of the existing methods.

Dissimilarity measure between intuitionistic Fuzzy sets and its applications in pattern recognition and clustering analysis

Maharishi Markandeshwar (Deemed To Be University)

Journal of Applied Mathematics, Statistics and Informatics

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this study, in order to prevent information loss, we propose two dissimilarity measures between intuitionistic fuzzy sets (IFSs), which consider membership...

Dissimilarity measure between intuitionistic Fuzzy sets and its applications in pattern recognition and clustering analysis

Online veröffentlicht: 09. Juni 2023

Seitenbereich: 61 - 77

DOI: https://doi.org/10.2478/jamsi-2023-0004

Schlüsselwörter
Intuitionistic fuzzy set, Dissimilarity measure, Distance measure, Similarity measure, Pattern recognition, Clustering analysis

© 2023 V. Rani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Dissimilarity measure between intuitionistic Fuzzy sets and its applications in pattern recognition and clustering analysis

Online veröffentlicht: 09. Juni 2023

Seitenbereich: 61 - 77

DOI: https://doi.org/10.2478/jamsi-2023-0004

SchlüsselwörterIntuitionistic fuzzy set, Dissimilarity measure, Distance measure, Similarity measure, Pattern recognition, Clustering analysis

© 2023 V. Rani et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Intuitionistic fuzzy set, Dissimilarity measure, Distance measure, Similarity measure, Pattern recognition, Clustering analysis