On similarity and entropy of neutrosophic sets

By Pinaki Majumdar, Syamal Kumar Samanta. Journal of Intelligent & Fuzzy Systems, 2013

453 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/e823ce9b152223cf75ca6564acadf0a65848162d

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In Management Science and Operations Research

In Mathematical Physics

Citations in the corpus

Interval Neutrosophic Sets and Their Application in Multicriteria Decision Making Problems (2014, background): “Majumdar and Samant introduced a measure of entropy of a SVNS [28].”
Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses (2015, background): “Majumdar and Samanta [7] introduced everal similarity measures of SVNSs based on distances, a matching function, membership grades, and then proposed an entropy measure or a SVNS.”
Relations on Interval Valued Neutrosophic Soft Sets (2014, background): “Majumdar and Samanta [31] proposed some types of similarity and entropy of neutrosophic sets, Broumi and Smarandache [16,17,18] proposed several similarity measures of neutrosophic sets.”
TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment (2014, background): “Majumdar and Samanta [23] studied similarity and entropy measure by incorporating euclidean distances of neutrosophic sets.”
Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems (2016, methodology): “Moreover, Majumdar and Samant (2014) introduced a measure of entropy of an SVNS. Wang, Smarandache, Zhang, and Sunderraman (2005) and Lupi´a˜nez (2009) proposed the concept of interval neutrosophic sets (INSs) and proposed the set-theoretic operators of INSs.”
Estimation of the joint roughness coefficient (JRC) of rock joints by vector similarity measures (2017, background): “In fact, the degree of similarity or dissimilarity between the objects under study has played an important role in various scientific fields, such as pattern recognition, machine learning, decision making, and image processing (Broumi and Smarandache 2013; Majumdar and Samanta 2014; Ye 2015).”
Hybrid Binary Logarithm Similarity Measure for MAGDM Problems under SVNS Assessments (2018, methodology): “In this section, we solve the problem with different existing strategies [33, 37, 38, 56].”