The Ordered Weighted Averaging Operators: Theory and Applications
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1997
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Aggregation plays a central role in many of the technological tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-cent.ered society, us is happening with the rapid growth of the Internet and the World Wirle Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that clearly has a strong aggregation-related component. More generally, in order to model the sophisticated ways in which human beings process information, as well as going beyond the human capa bilities, we need provide a basket of aggregation tools. The centrality of aggregation in human thought can be be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum and the simple average |
| Beschreibung: | 1 Online-Ressource (X, 347 p) |
| ISBN: | 9781461561231 9781461378068 |
| DOI: | 10.1007/978-1-4615-6123-1 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV042420915 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 150317s1997 |||| o||u| ||||||eng d | ||
| 020 | |a 9781461561231 |c Online |9 978-1-4615-6123-1 | ||
| 020 | |a 9781461378068 |c Print |9 978-1-4613-7806-8 | ||
| 024 | 7 | |a 10.1007/978-1-4615-6123-1 |2 doi | |
| 035 | |a (OCoLC)863683871 | ||
| 035 | |a (DE-599)BVBBV042420915 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
| 082 | 0 | |a 511.3 |2 23 | |
| 084 | |a MAT 000 |2 stub | ||
| 100 | 1 | |a Yager, Ronald R. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a The Ordered Weighted Averaging Operators |b Theory and Applications |c edited by Ronald R. Yager, Janusz Kacprzyk |
| 264 | 1 | |a Boston, MA |b Springer US |c 1997 | |
| 300 | |a 1 Online-Ressource (X, 347 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Aggregation plays a central role in many of the technological tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-cent.ered society, us is happening with the rapid growth of the Internet and the World Wirle Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that clearly has a strong aggregation-related component. More generally, in order to model the sophisticated ways in which human beings process information, as well as going beyond the human capa bilities, we need provide a basket of aggregation tools. The centrality of aggregation in human thought can be be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum and the simple average | ||
| 650 | 4 | |a Mathematics | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Information Systems | |
| 650 | 4 | |a Logic, Symbolic and mathematical | |
| 650 | 4 | |a Mathematical Logic and Foundations | |
| 650 | 4 | |a Artificial Intelligence (incl. Robotics) | |
| 650 | 4 | |a Management of Computing and Information Systems | |
| 650 | 4 | |a Künstliche Intelligenz | |
| 650 | 4 | |a Mathematik | |
| 700 | 1 | |a Kacprzyk, Janusz |e Sonstige |4 oth | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4615-6123-1 |x Verlag |3 Volltext |
| 912 | |a ZDB-2-SMA |a ZDB-2-BAE | ||
| 940 | 1 | |q ZDB-2-SMA_Archive | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027856332 | ||
Datensatz im Suchindex
| _version_ | 1804153093400559616 |
|---|---|
| any_adam_object | |
| author | Yager, Ronald R. |
| author_facet | Yager, Ronald R. |
| author_role | aut |
| author_sort | Yager, Ronald R. |
| author_variant | r r y rr rry |
| building | Verbundindex |
| bvnumber | BV042420915 |
| classification_tum | MAT 000 |
| collection | ZDB-2-SMA ZDB-2-BAE |
| ctrlnum | (OCoLC)863683871 (DE-599)BVBBV042420915 |
| dewey-full | 511.3 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 511 - General principles of mathematics |
| dewey-raw | 511.3 |
| dewey-search | 511.3 |
| dewey-sort | 3511.3 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4615-6123-1 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02776nmm a2200469zc 4500</leader><controlfield tag="001">BV042420915</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s1997 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781461561231</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4615-6123-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781461378068</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-4613-7806-8</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4615-6123-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)863683871</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042420915</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">511.3</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yager, Ronald R.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">The Ordered Weighted Averaging Operators</subfield><subfield code="b">Theory and Applications</subfield><subfield code="c">edited by Ronald R. Yager, Janusz Kacprzyk</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boston, MA</subfield><subfield code="b">Springer US</subfield><subfield code="c">1997</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (X, 347 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Aggregation plays a central role in many of the technological tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-cent.ered society, us is happening with the rapid growth of the Internet and the World Wirle Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that clearly has a strong aggregation-related component. More generally, in order to model the sophisticated ways in which human beings process information, as well as going beyond the human capa bilities, we need provide a basket of aggregation tools. The centrality of aggregation in human thought can be be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum and the simple average</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Information Systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Logic, Symbolic and mathematical</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical Logic and Foundations</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial Intelligence (incl. Robotics)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Management of Computing and Information Systems</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kacprzyk, Janusz</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4615-6123-1</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027856332</subfield></datafield></record></collection> |
| id | DE-604.BV042420915 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:07Z |
| institution | BVB |
| isbn | 9781461561231 9781461378068 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856332 |
| oclc_num | 863683871 |
| open_access_boolean | |
| owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| physical | 1 Online-Ressource (X, 347 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 1997 |
| publishDateSearch | 1997 |
| publishDateSort | 1997 |
| publisher | Springer US |
| record_format | marc |
| spelling | Yager, Ronald R. Verfasser aut The Ordered Weighted Averaging Operators Theory and Applications edited by Ronald R. Yager, Janusz Kacprzyk Boston, MA Springer US 1997 1 Online-Ressource (X, 347 p) txt rdacontent c rdamedia cr rdacarrier Aggregation plays a central role in many of the technological tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-cent.ered society, us is happening with the rapid growth of the Internet and the World Wirle Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that clearly has a strong aggregation-related component. More generally, in order to model the sophisticated ways in which human beings process information, as well as going beyond the human capa bilities, we need provide a basket of aggregation tools. The centrality of aggregation in human thought can be be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum and the simple average Mathematics Artificial intelligence Information Systems Logic, Symbolic and mathematical Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Management of Computing and Information Systems Künstliche Intelligenz Mathematik Kacprzyk, Janusz Sonstige oth https://doi.org/10.1007/978-1-4615-6123-1 Verlag Volltext |
| spellingShingle | Yager, Ronald R. The Ordered Weighted Averaging Operators Theory and Applications Mathematics Artificial intelligence Information Systems Logic, Symbolic and mathematical Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Management of Computing and Information Systems Künstliche Intelligenz Mathematik |
| title | The Ordered Weighted Averaging Operators Theory and Applications |
| title_auth | The Ordered Weighted Averaging Operators Theory and Applications |
| title_exact_search | The Ordered Weighted Averaging Operators Theory and Applications |
| title_full | The Ordered Weighted Averaging Operators Theory and Applications edited by Ronald R. Yager, Janusz Kacprzyk |
| title_fullStr | The Ordered Weighted Averaging Operators Theory and Applications edited by Ronald R. Yager, Janusz Kacprzyk |
| title_full_unstemmed | The Ordered Weighted Averaging Operators Theory and Applications edited by Ronald R. Yager, Janusz Kacprzyk |
| title_short | The Ordered Weighted Averaging Operators |
| title_sort | the ordered weighted averaging operators theory and applications |
| title_sub | Theory and Applications |
| topic | Mathematics Artificial intelligence Information Systems Logic, Symbolic and mathematical Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Management of Computing and Information Systems Künstliche Intelligenz Mathematik |
| topic_facet | Mathematics Artificial intelligence Information Systems Logic, Symbolic and mathematical Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Management of Computing and Information Systems Künstliche Intelligenz Mathematik |
| url | https://doi.org/10.1007/978-1-4615-6123-1 |
| work_keys_str_mv | AT yagerronaldr theorderedweightedaveragingoperatorstheoryandapplications AT kacprzykjanusz theorderedweightedaveragingoperatorstheoryandapplications |