Automating Data-Driven Modelling of Dynamical Systems An Evolutionary Computation Approach
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Sprache:Englisch
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Produktdetails
Format
Kopierschutz
Nein
Family Sharing
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Erscheinungsdatum
03.02.2022
Verlag
Springer Nature SwitzerlandSeitenzahl
229 (Printausgabe)
Dateigröße
11357 KB
Sprache
Englisch
EAN
9783030903435
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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