Cosine similarity measures for intuitionistic fuzzy sets and their applications

By Jun Ye. Mathematical and computer modelling, 2011

657 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/996b8c018503ee76cb558183a8f9e3fddadff1f0

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. Man Huang
2. Qiqiang Liang
3. Rui Yong
4. Shigui Du
5. Jun Ye

In Management Science and Operations Research

1. Man Huang
2. Qiqiang Liang
3. Rui Yong
4. Shigui Du
5. Jun Ye
6. Harish Garg
7. Surapati Pramanik
8. Bibhas Chandra Giri

In Statistics and Probability

1. Man Huang
2. Qiqiang Liang
3. Rui Yong
4. Shigui Du
5. Jun Ye
6. Harish Garg
7. Dengfeng Li
8. David A. Wood

Citations in the corpus

• Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment (2013, methodology): “Based on the cosine similarity measure (Ye, 2011), the cosine similarity measure between SVNSs A and B is defined as follows: According to the value range of the cosine function, we can obtain the following property: 0 # S ð A ; B Þ # 1 : Hence, there is 0 # K ( A , B ) # 1 for i ¼ 1 because S ( A ,…”
• Estimation of the joint roughness coefficient (JRC) of rock joints by vector similarity measures (2017, methodology): “Vector similarity measures (VSMs) are especially useful in pattern recognition (Ye 2011).”