Automating Data-Driven Modelling of Dynamical Systems
An Evolutionary Computation Approach
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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.
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.
Presents a novel approach for automating system identification Offers novel solutions to multi-criteria system identification problems Reviews fundamental concepts of system identification
Autor*in
Dhruv Khandelwal
Themen in »Automating Data-Driven Modelling of Dynamical Systems«
Automated System Identification Multi-criteria model selection Model Selection Problem User-specified Performance Measures Parametric Model Representation Multi-objective Optimization Problem Bi-level Optimization Grammar-based Model Representation Grammar-based Identification Evolutionary algorithms in System Identification Symbolic Regression for Dynamical Systems Memetic Algorithm Non-linear Model Selection