Automating Data-Driven Modelling of Dynamical Systems - An Evolutionary Computation Approach (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Theses
Release date:	February 2022
First published:	2022
Authors:	Dhruv Khandelwal
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	229
Edition:	1st ed. 2022
ISBN-13:	978-3-03-090342-8
Categories:	Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General Promotions
LSN:	3-03-090342-7
Barcode:	9783030903428

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