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Erschienen in: Neural Computing and Applications 7/2020

01.01.2019 | Original Article

Bipolar \(\delta\)-equal complex fuzzy concept lattice with its application

verfasst von: Prem Kumar Singh

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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Abstract

Recently, bipolar as well as vague concept lattice visualization is introduced for precise representation of inconsistency and incompleteness in data sets based on its acceptation and rejection part simultaneously. In this process, a problem is addressed while measuring the periodic fluctuation in bipolar information at the given phase of time. This changes in human cognition used coexist often in our daily life where the sentiments (i.e., love or hatred) for anyone may change several times from morning to evening office time. In this case precise representation of this type of bipolar information and measuring its pattern is a major issue for the researchers. To deal with this problem, the current paper proposes three methods for adequate representation of bipolar complex data set using the calculus of complex fuzzy matrix, \(\delta\)-equality and the calculus of granular computing, respectively. Hence, the proposed method provides an umbrella way to navigate or decompose the bipolar complex data sets and their semantics using an illustrative example. The results obtained from the proposed methods are also compared to validate the results.

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Metadaten
Titel
Bipolar -equal complex fuzzy concept lattice with its application
verfasst von
Prem Kumar Singh
Publikationsdatum
01.01.2019
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3936-9

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