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Some distances, similarity and entropy measures for interval-valued neutrosophic sets and their relationship
- Source :
- International Journal of Machine Learning and Cybernetics. 10:347-355
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- This paper proposes some new distance measures between interval-valued neutrosophic sets (IvNSs) and their similarity measures. Then, some entropy measures of IvNS based on the distances are proposed as the extension of the entropy measures of interval-valued intuitionistic fuzzy sets (IvIFSs). Also, we investigate the relationship between the presented entropy measures and the similarity measures for IvNSs. Finally, the comparison of the new entropy measures with existing entropy measures for IvNSs is given by the numerical and decision-making examples to demonstrate that the proposed new entropy measures for IvNSs are effective and reasonable and more intelligible in representing the degree of fuzziness of IvNSs than the existing ones.
- Subjects :
- 0209 industrial biotechnology
business.industry
Principle of maximum entropy
Pattern recognition
02 engineering and technology
Joint entropy
Distance measures
Information diagram
Rényi entropy
020901 industrial engineering & automation
Cross entropy
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
Entropy (information theory)
Applied mathematics
020201 artificial intelligence & image processing
Transfer entropy
Computer Vision and Pattern Recognition
Artificial intelligence
business
Software
Mathematics
Subjects
Details
- ISSN :
- 1868808X and 18688071
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- International Journal of Machine Learning and Cybernetics
- Accession number :
- edsair.doi...........f28275f886dee2ae301d972db6c89efa