Buch, Englisch, 229 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 394 g
Reihe: Springer Theses
An Evolutionary Computation Approach
Buch, Englisch, 229 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 394 g
Reihe: Springer Theses
ISBN: 978-3-030-90345-9
Verlag: Springer International Publishing
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Introduction.- The State-of-the-art.- Preliminaries - Evolutionary Algorithms.- Tree Adjoining Grammar.- Performance measures.
