Bipolar fuzzy concepts reduction using granular-based weighted entropy
Abstract The bipolar fuzzy concept lattice has given a way to analyze the uncertainty in soft data set beyond the unipolar space. In this process, a problem is addressed while dealing with large number of bipolar fuzzy concepts and its importance for adequate decision-making process. It may create r...
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| Autor*in: |
Singh, Prem Kumar [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Soft computing - Springer Berlin Heidelberg, 1997, 26(2022), 19 vom: 15. Juli, Seite 9859-9871 |
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| Übergeordnetes Werk: |
volume:26 ; year:2022 ; number:19 ; day:15 ; month:07 ; pages:9859-9871 |
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| DOI / URN: |
10.1007/s00500-022-07336-w |
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OLC2079513702 |
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10.1007/s00500-022-07336-w doi (DE-627)OLC2079513702 (DE-He213)s00500-022-07336-w-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Singh, Prem Kumar verfasserin (orcid)0000-0003-1465-6572 aut Bipolar fuzzy concepts reduction using granular-based weighted entropy 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract The bipolar fuzzy concept lattice has given a way to analyze the uncertainty in soft data set beyond the unipolar space. In this process, a problem is addressed while dealing with large number of bipolar fuzzy concepts and its importance for adequate decision-making process. It may create randomness in the decision due to bipolarity and its existence in customer feedback, or expert opinion. To overcome from this issue, the current paper tried to measure the randomness in bipolar fuzzy concepts using the properties of Shannon entropy. The importance of bipolar fuzzy concept is decided based on defined window of granulation ($$\alpha _1, \alpha _2$$) for its computed weight with an illustrative example. The obtained results are also compared with recently available approaches on data with bipolar fuzzy attributes for validation. Bipolar fuzzy set Bipolar fuzzy concept Formal fuzzy concept Fuzzy concept lattice Granular computing Soft data Uncertainty measurement Enthalten in Soft computing Springer Berlin Heidelberg, 1997 26(2022), 19 vom: 15. Juli, Seite 9859-9871 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:26 year:2022 number:19 day:15 month:07 pages:9859-9871 https://doi.org/10.1007/s00500-022-07336-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 26 2022 19 15 07 9859-9871 |
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Abstract The bipolar fuzzy concept lattice has given a way to analyze the uncertainty in soft data set beyond the unipolar space. In this process, a problem is addressed while dealing with large number of bipolar fuzzy concepts and its importance for adequate decision-making process. It may create randomness in the decision due to bipolarity and its existence in customer feedback, or expert opinion. To overcome from this issue, the current paper tried to measure the randomness in bipolar fuzzy concepts using the properties of Shannon entropy. The importance of bipolar fuzzy concept is decided based on defined window of granulation ($$\alpha _1, \alpha _2$$) for its computed weight with an illustrative example. The obtained results are also compared with recently available approaches on data with bipolar fuzzy attributes for validation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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Abstract The bipolar fuzzy concept lattice has given a way to analyze the uncertainty in soft data set beyond the unipolar space. In this process, a problem is addressed while dealing with large number of bipolar fuzzy concepts and its importance for adequate decision-making process. It may create randomness in the decision due to bipolarity and its existence in customer feedback, or expert opinion. To overcome from this issue, the current paper tried to measure the randomness in bipolar fuzzy concepts using the properties of Shannon entropy. The importance of bipolar fuzzy concept is decided based on defined window of granulation ($$\alpha _1, \alpha _2$$) for its computed weight with an illustrative example. The obtained results are also compared with recently available approaches on data with bipolar fuzzy attributes for validation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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Abstract The bipolar fuzzy concept lattice has given a way to analyze the uncertainty in soft data set beyond the unipolar space. In this process, a problem is addressed while dealing with large number of bipolar fuzzy concepts and its importance for adequate decision-making process. It may create randomness in the decision due to bipolarity and its existence in customer feedback, or expert opinion. To overcome from this issue, the current paper tried to measure the randomness in bipolar fuzzy concepts using the properties of Shannon entropy. The importance of bipolar fuzzy concept is decided based on defined window of granulation ($$\alpha _1, \alpha _2$$) for its computed weight with an illustrative example. The obtained results are also compared with recently available approaches on data with bipolar fuzzy attributes for validation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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| doi_str |
10.1007/s00500-022-07336-w |
| up_date |
2024-07-04T01:12:14.851Z |
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