On the Dengfeng-Chuntian similarity measure and its application to pattern recognition
By H. Mitchell. Pattern Recognition Letters, 2003
391 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/8b265febfc734186862c1350c1de301c734df342
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Citations in the corpus
- Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets (2013, methodology): “Similarity and distance measures have been widely applied in many fields such as multicriteria decision-making [5,21], group decision [27,33], grey relational analysis [26], pattern recognition [11,14], image processing [15], and cluster analysis [37].”
- Cosine similarity measures for intuitionistic fuzzy sets and their applications (2011, background): “Furthermore, Mitchell [9] interpreted IFSs as ensembles of ordered fuzzy sets from a statistical viewpoint to modify Li and Cheng’s measures.”
- Intuitionistic Fuzzy Information Measures with Application in Rating of Township Development (2016, methodology): “Liang and Shi [24] and Mitchell [31] enhanced the similarity measure of IFS developed by [21]; Szmidt and Kacprzyk [33] applied the similarity measure of IFS in group decision making.”
- Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group (2009, background): “Especially, many authors have paid considerable attention to the research on similarity measures and distance measures between intuitionistic fuzzy sets (IFSs) (Grzegorzewski et al. 2004; Hung and Yang 2004; Hwang and Yoon 1981; Li and Cheng 2002; Mitchell 2003; Szmidt and Kacprzyk 2000, 2004a,b).”
- Intuitionistic fuzzy information - Applications to pattern recognition (2007, methodology): “In order to demonstrate the application of the introduced symmetric discrimination information measure for IFSs to pattern recognition, we considered the problem discussed in Dengfeng and Chuntian (2002) and Mitchell (2003). We are given three known patterns P1, P2 and P3, which have classifications”
- 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.”
- Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance (2004, methodology): “On the other hand, Mitchell (2003) interpreted IFSs as ensembles of ordered fuzzy sets from a statistical viewpoint to modify Li and Cheng’s methods.”
- Hesitant fuzzy entropy and cross‐entropy and their use in multiattribute decision‐making (2012, neutral): “S4(ηα, γα) = max i {|ασ (i) + ασ (lα−i+1) − 1|} (29)”
- Handbook of Granular Computing (2008, methodology): “It is worthwhile to mention that a rough set approach to the approximation of compound concepts has been developed and at this time no traditional method is able to directly approximate compound concepts [103, 104].”
- Distance and similarity measures for hesitant fuzzy sets (2011, methodology): “Some authors [17,24,29,30,35,39] improved Li and Cheng’ method [15].”