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hardcover. Condition: Gut. 452 Seiten; 9781441980199.3 Gewicht in Gramm: 1.
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Evolving Fuzzy Models: Incremental Learning,.
Language: English
Published by VDM Verlag Dr. Müller, 2008
ISBN 10: 383648465X ISBN 13: 9783836484657
Condition: New.
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![Stock image for Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications [Hardcover] Lughofer, Edwin and Sayed-Mouchaweh, Moamar for sale by SpringBooks](https://pictures.abebooks.com/isbn/9783030056445-us-300.jpg)
Hardcover. Condition: Very Good. 1. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.
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Evolving Fuzzy Models
Language: English
Published by VDM Verlag Dr. Müller E.K. Nov 2013, 2013
ISBN 10: 383648465X ISBN 13: 9783836484657
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -Nowadays data-driven models become more and more an essential part in industrial systems for application tasks such as system identification and analysis, prediction, control or fault detection. Data driven models are mathematical models which are completely identified from data, which can be available in form of offline data sets, most commonly stored in data matrices, or in form of online measurements. Data-driven models possess the nice property that they can be built up generically in the sense that no underlying physical, chemical etc. laws about the system variables have to be known. Whenever measurements are recorded online with a certain frequency, usually the models should be kept up-to-date, especially when new system states occur during online production processes. This requires an adaptation of model parameters and an evolution of model structures with incremental learning steps, as a complete rebuilding from time to time with all recorded measurements would not terminate in real-time. The book addresses the on-line evolution of fuzzy models and underlines its necessity by concrete application examples from on-line quality control systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch.
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 452 | Sprache: Englisch | Produktart: Bücher | Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy. Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations. This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research. .
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Evolving Fuzzy Models: Incremental Learning, Interpretability And Stability Issues, Applications
Language: English
Published by Vdm Verlag Dr. Müller, 2008
ISBN 10: 383648465X ISBN 13: 9783836484657
US$ 138.80
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 156 pages. 8.66x5.91x0.36 inches. In Stock.
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Evolving fuzzy systems - methodologies, advanced concepts and applications. Studies in fuzziness and soft computing ; Vol. 266.
Book 60 of 183: Studies in Fuzziness and Soft ComputingLanguage: English
Published by Berlin ; Heidelberg : Springer, 2011
ISBN 10: 3642180868 ISBN 13: 9783642180866
Seller: Druckwaren Antiquariat, Salzwedel, Germany
Association Member: GIAQ
Seller rating 5 out of 5 stars
OPp., gebundene Ausgabe. Condition: Gut. XXIV, 454 S.: graph. Darst. ; 24 cm, Cover with little wear, good condition. ISBN: 9783642180866 Altersfreigabe FSK ab 0 Jahre Sprache: Englisch Gewicht in Gramm: 1050.
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Learning in Non-Stationary Environments: Methods and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 186.32
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Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 186.32
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Learning in Non-Stationary Environments: Methods and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 186.32
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Learning in Non-Stationary Environments : Methods and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 186.31
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 480 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 480 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Learning in Non-Stationary Environments
Language: English
Published by Springer New York, Springer US Apr 2012, 2012
ISBN 10: 1441980199 ISBN 13: 9781441980199
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences.Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy.Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations.This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 452 pp. Englisch.
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Predictive Maintenance In Dynamic Syste
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications
Book 60 of 183: Studies in Fuzziness and Soft ComputingLanguage: English
Published by Springer Berlin Heidelberg, 2013
ISBN 10: 3642266924 ISBN 13: 9783642266928
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Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications (Studies in Fuzziness and Soft Computing, 266)
Book 60 of 183: Studies in Fuzziness and Soft ComputingSeller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 255.69
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Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications (Studies in Fuzziness and Soft Computing, 266)
Book 60 of 183: Studies in Fuzziness and Soft ComputingSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 255.69
US$ 16.14 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Learning in Non-Stationary Environments : Methods and Applications
Language: English
Published by Springer New York, Springer New York, 2014
ISBN 10: 1489993401 ISBN 13: 9781489993403
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dynamic learning methods serve as keystones for achieving models with high accuracy. Rather than rely on a mathematical theorem/proof style, the editors highlight numerous figures, tables, examples and applications, together with their explanations. This approach offers a useful basis for further investigation and fresh ideas and motivates and inspires newcomers to explore this promising and still emerging field of research.
