Rough fuzzy bipolar soft sets and application in decision-making problems
Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Malik, Nosheen [verfasserIn] |
|---|
| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag GmbH Germany 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Soft computing - Springer Berlin Heidelberg, 1997, 23(2017), 5 vom: 25. Okt., Seite 1603-1614 |
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| Übergeordnetes Werk: |
volume:23 ; year:2017 ; number:5 ; day:25 ; month:10 ; pages:1603-1614 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00500-017-2883-1 |
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OLC2034895185 |
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| 520 | |a Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example. | ||
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10.1007/s00500-017-2883-1 doi (DE-627)OLC2034895185 (DE-He213)s00500-017-2883-1-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Malik, Nosheen verfasserin aut Rough fuzzy bipolar soft sets and application in decision-making problems 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany 2017 Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example. Rough sets Approximation space Fuzzy sets Bipolar information Fuzzy bipolar soft sets Shabir, Muhammad aut Enthalten in Soft computing Springer Berlin Heidelberg, 1997 23(2017), 5 vom: 25. Okt., Seite 1603-1614 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:23 year:2017 number:5 day:25 month:10 pages:1603-1614 https://doi.org/10.1007/s00500-017-2883-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 23 2017 5 25 10 1603-1614 |
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Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example. © Springer-Verlag GmbH Germany 2017 |
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Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example. © Springer-Verlag GmbH Germany 2017 |
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Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example. © Springer-Verlag GmbH Germany 2017 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2034895185</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502112029.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00500-017-2883-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2034895185</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00500-017-2883-1-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">11</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Malik, Nosheen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Rough fuzzy bipolar soft sets and application in decision-making problems</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag GmbH Germany 2017</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The rough set theory is a successful tool to study the vagueness in data, while the fuzzy bipolar soft sets have ability to handle the uncertainty, as well as bipolarity of the information in many situations. We connect the Pawlak’s rough sets with the fuzzy bipolar soft sets and introduce the concept of rough fuzzy bipolar soft sets. We also examine some structural properties of rough fuzzy bipolar soft sets and study the effects of the equivalence relation in Pawlak approximation space on the roughness of the fuzzy bipolar soft sets. We also discuss some similarity relations among the fuzzy bipolar soft sets, based on their roughness. At the end, an application of the rough fuzzy bipolar soft sets in a decision-making problem is discussed and an algorithm for this application is proposed, supported by an example.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Rough sets</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Approximation space</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fuzzy sets</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bipolar information</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fuzzy bipolar soft sets</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shabir, Muhammad</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Soft computing</subfield><subfield code="d">Springer Berlin Heidelberg, 1997</subfield><subfield code="g">23(2017), 5 vom: 25. 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