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Beschreibung
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.
An Evolutionary Computation Approach
An Evolutionary Computation Approach
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 04. Februar 2022 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 501 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783030903428 |
| Seiten | 229 |
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