£113.25

Springer Automating Data-Driven Modelling of Dynamical Systems

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Description

Explore advanced computational methods with Automating Data-Driven Modelling of Dynamical Systems: An Evolutionary Computation Approach. Published by Springer as part of the Springer Theses series, this academic work focuses on the intersection of evolutionary computation and dynamical systems modelling. This book provides a specialized look at how data-driven techniques can be used to automate the modelling of complex systems. It is designed for researchers and professionals working within the fields of computer science, artificial intelligence, and machine learning. By focusing on evolutionary computation, the text offers a unique perspective on solving problems related to dynamical systems through automated, data-centric processes. Whether you are studying advanced AI or looking for specific methodologies in computational modeling, this Springer publication serves as a technical resource for understanding modern approaches to system dynamics. It fits into essential academic collections for those specializing in computing and internet-based computer science research.

Key Features

Part of the respected Springer Theses series, providing high-quality academic research for students and professionals.

Focuses on evolutionary computation approaches to enhance the automation of dynamical systems modelling.

Provides deep insights into data-driven methodologies within the field of computer science.

A specialized resource for those studying artificial intelligence and machine learning applications.

Designed for researchers seeking advanced technical knowledge in computational and dynamical systems.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
04 February 2023
Listed Since
12 January 2023

Barcode

No barcode data available

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