Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems
The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an origi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg
Physica-Verlag HD
2002
|
| Schriftenreihe: | Studies in Fuzziness and Soft Computing
92 |
| Schlagworte: | |
| Online-Zugang: | FHI01 BTU01 URL des Erstveröffentlichers |
| Zusammenfassung: | The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems |
| Beschreibung: | 1 Online-Ressource (XIII, 214 p) |
| ISBN: | 9783790817942 |
| DOI: | 10.1007/978-3-7908-1794-2 |
Internformat
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| 520 | |a The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems | ||
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Datensatz im Suchindex
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| author | Angelov, Plamen P. |
| author_facet | Angelov, Plamen P. |
| author_role | aut |
| author_sort | Angelov, Plamen P. |
| author_variant | p p a pp ppa |
| building | Verbundindex |
| bvnumber | BV045149544 |
| collection | ZDB-2-ENG |
| ctrlnum | (ZDB-2-ENG)978-3-7908-1794-2 (OCoLC)1184499085 (DE-599)BVBBV045149544 |
| 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 | 10.1007/978-3-7908-1794-2 |
| format | Electronic eBook |
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| id | DE-604.BV045149544 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:04Z |
| institution | BVB |
| isbn | 9783790817942 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030539242 |
| oclc_num | 1184499085 |
| open_access_boolean | |
| owner | DE-573 DE-634 |
| owner_facet | DE-573 DE-634 |
| physical | 1 Online-Ressource (XIII, 214 p) |
| psigel | ZDB-2-ENG ZDB-2-ENG_2000/2004 ZDB-2-ENG ZDB-2-ENG_2000/2004 ZDB-2-ENG ZDB-2-ENG_Archiv |
| publishDate | 2002 |
| publishDateSearch | 2002 |
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| publisher | Physica-Verlag HD |
| record_format | marc |
| series2 | Studies in Fuzziness and Soft Computing |
| spelling | Angelov, Plamen P. Verfasser aut Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems by Plamen P. Angelov Heidelberg Physica-Verlag HD 2002 1 Online-Ressource (XIII, 214 p) txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 92 The objects of modelling and control change due to dynamical characteristics, fault development or simply ageing. There is a need to up-date models inheriting useful structure and parameter information. The book gives an original solution to this problem with a number of examples. It treats an original approach to on-line adaptation of rule-based models and systems described by such models. It combines the benefits of fuzzy rule-based models suitable for the description of highly complex systems with the original recursive, non iterative technique of model evolution without necessarily using genetic algorithms, thus avoiding computational burden making possible real-time industrial applications. Potential applications range from autonomous systems, on-line fault detection and diagnosis, performance analysis to evolving (self-learning) intelligent decision support systems Mathematics Mathematical Logic and Foundations Systems Theory, Control Artificial Intelligence (incl. Robotics) Complexity Artificial intelligence System theory Mathematical logic Complexity, Computational Fuzzy-Logik (DE-588)4341284-1 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Fuzzy-Logik (DE-588)4341284-1 s 1\p DE-604 Künstliche Intelligenz (DE-588)4033447-8 s 2\p DE-604 Erscheint auch als Druck-Ausgabe 9783790825060 https://doi.org/10.1007/978-3-7908-1794-2 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Angelov, Plamen P. Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems Mathematics Mathematical Logic and Foundations Systems Theory, Control Artificial Intelligence (incl. Robotics) Complexity Artificial intelligence System theory Mathematical logic Complexity, Computational Fuzzy-Logik (DE-588)4341284-1 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| subject_GND | (DE-588)4341284-1 (DE-588)4033447-8 |
| title | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems |
| title_auth | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems |
| title_exact_search | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems |
| title_full | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems by Plamen P. Angelov |
| title_fullStr | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems by Plamen P. Angelov |
| title_full_unstemmed | Evolving Rule-Based Models A Tool for Design of Flexible Adaptive Systems by Plamen P. Angelov |
| title_short | Evolving Rule-Based Models |
| title_sort | evolving rule based models a tool for design of flexible adaptive systems |
| title_sub | A Tool for Design of Flexible Adaptive Systems |
| topic | Mathematics Mathematical Logic and Foundations Systems Theory, Control Artificial Intelligence (incl. Robotics) Complexity Artificial intelligence System theory Mathematical logic Complexity, Computational Fuzzy-Logik (DE-588)4341284-1 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Mathematics Mathematical Logic and Foundations Systems Theory, Control Artificial Intelligence (incl. Robotics) Complexity Artificial intelligence System theory Mathematical logic Complexity, Computational Fuzzy-Logik Künstliche Intelligenz |
| url | https://doi.org/10.1007/978-3-7908-1794-2 |
| work_keys_str_mv | AT angelovplamenp evolvingrulebasedmodelsatoolfordesignofflexibleadaptivesystems |