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Fuzzy data analysis
Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
Springer
1992
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-94-011-2506-2 http://cds.cern.ch/record/2146602 |
_version_ | 1780950368647118848 |
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author | Bandemer, Hans Näther, Wolfgang |
author_facet | Bandemer, Hans Näther, Wolfgang |
author_sort | Bandemer, Hans |
collection | CERN |
description | Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics. |
id | cern-2146602 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 1992 |
publisher | Springer |
record_format | invenio |
spelling | cern-21466022021-04-21T19:43:17Zdoi:10.1007/978-94-011-2506-2http://cds.cern.ch/record/2146602engBandemer, HansNäther, WolfgangFuzzy data analysisMathematical Physics and MathematicsFuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.Springeroai:cds.cern.ch:21466021992 |
spellingShingle | Mathematical Physics and Mathematics Bandemer, Hans Näther, Wolfgang Fuzzy data analysis |
title | Fuzzy data analysis |
title_full | Fuzzy data analysis |
title_fullStr | Fuzzy data analysis |
title_full_unstemmed | Fuzzy data analysis |
title_short | Fuzzy data analysis |
title_sort | fuzzy data analysis |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-94-011-2506-2 http://cds.cern.ch/record/2146602 |
work_keys_str_mv | AT bandemerhans fuzzydataanalysis AT natherwolfgang fuzzydataanalysis |