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Automating Data-Driven Modelling of Dynamical Systems: An Evolutionary Computation Approach (Springer Theses) - Softcover
Inhaltsangabe
This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user’s perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.
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This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user's perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.
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- VerlagSpringer
- Erscheinungsdatum2023
- ISBN 10 3030903451
- ISBN 13 9783030903459
- EinbandTapa blanda
- SpracheEnglisch
- Auflage1
- Anzahl der Seiten256
- Kontakt zum HerstellerNicht verfügbar
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Automating Data-Driven Modelling of Dynamical Systems
Verlag:
Springer International Publishing, 2023
ISBN 10: 3030903451
ISBN 13: 9783030903459
Neu
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Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a novel approach for automating system identificationOffers novel solutions to multi-criteria system identification problemsReviews fundamental concepts of system identificationThis book describes a user-friendly, evolut. Bestandsnummer des Verkäufers 795423258
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Automating Data-Driven Modelling of Dynamical Systems
ISBN 10: 3030903451
ISBN 13: 9783030903459
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. Neuware -This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user¿s perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch. Bestandsnummer des Verkäufers 9783030903459
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Automating Data-Driven Modelling of Dynamical Systems : An Evolutionary Computation Approach
Verlag:
Springer International Publishing, 2023
ISBN 10: 3030903451
ISBN 13: 9783030903459
Neu
Taschenbuch
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Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user's perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification. Bestandsnummer des Verkäufers 9783030903459
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Automating Data-Driven Modelling of Dynamical Systems
Verlag:
Springer International Publishing Feb 2023, 2023
ISBN 10: 3030903451
ISBN 13: 9783030903459
Neu
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user's perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification. 256 pp. Englisch. Bestandsnummer des Verkäufers 9783030903459
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