Similarity measures on intuitionistic fuzzy sets

By Zhizhen Liang, Pengfei Shi. Pattern Recognition Letters, 2003

458 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/58b0f5c532271d675d4432611a109fd69d6aa55e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zeshui Xu
2. Meimei Xia
3. Xindong Peng
4. Yong Yang
5. Jun Ye
6. Harish Garg
7. Huiyong Yuan
8. Vladik Kreinovich

In Management Science and Operations Research

1. Xindong Peng
2. Harish Garg
3. Zeshui Xu
4. Meimei Xia
5. Yong Yang
6. Peide Liu
7. Huiyong Yuan
8. Jun Ye

Citations in the corpus

• Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance (2004, methodology): “Example 1 (Liang and Shi, 2003).”
• Pythagorean Fuzzy Information Measures and Their Applications (2017, result): “58 to compare the experimental results of the proposed similarity measure S 1 with the existing similarity measures, 17,31–33, 39, 41– 43,46,47,58 as shown in Table II.”
• Cosine similarity measures for intuitionistic fuzzy sets and their applications (2011, background): “Later, Liang and Shi [8] proposed several similarity measures to differentiate different IFSs and discussed the relationships between these measures.”
• Distance and similarity measures for hesitant fuzzy sets (2011, methodology): “Some authors [17,24,29,30,35,39] improved Li and Cheng’ method [15].”
• Hesitant fuzzy entropy and cross‐entropy and their use in multiattribute decision‐making (2012, unknown): “S3(ηα, γα) = 1 − p √√√√ −−− [ 2 lα ] −−−− [lα / 2] |ασ (i)+ασ (lα−i+1)−1|p ∑ i=1 (28)”
• A Novel Correlation Coefficients between Pythagorean Fuzzy Sets and Its Applications to Decision‐Making Processes (2016, methodology): “Under these environment, the correlation coefficient has been applied in many fields such as image processing, 3,4 clustering analysis, 5 pattern recognition, 6 and decision making.”
• Handbook of Granular Computing (2008, methodology): “The rough inclusion relation can also be used for function approximation and relation approximation [102].”