Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

ISBN-10: 110838658X
ISBN-13: 9781108386586
Category: Computers
Language: English
Published: 2019-02-28
Publisher: Cambridge University Press
Authors: Steven L. Brunton, J. Nathan Kutz

Description

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.

Get the book

Other editions

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
- 2022-05-05
- 615 pages
- Paperback
- Cambridge University Press
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
- 2022-04-30
- - pages
- Ebook
- Cambridge University Press
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
- 2019-02-28
- 500 pages
- Paperback
- Cambridge University Press

Similar books

Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data
By J. Nathan Kutz
Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the ...
Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems
By Steven L. Brunton, J. Nathan Kutz, Bingni W. Brunton
This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known.
Machine Learning Control – Taming Nonlinear Dynamics and Turbulence
By Thomas Duriez, Steven L. Brunton, Bernd R. Noack
N. Gautier, J.-L. Aider, T. Duriez, B.R. Noack, M. Segond, M.W. Abel, Closed-loop separation control using machine learning. ... 10(6), 455–464 (2006) D.E. Goldberg, Genetic Algorithms (Pearson Education India, 2006) D. Greenblatt, ...
Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory
By Hubert Rehborn, Micha Koller, Stefan Kaufmann
This book offers a unique, data-driven analysis of vehicular traffic in traffic networks, also considering how to apply data-driven insights to the intelligent transport systems of the future.
Informatics for Materials Science and Engineering: Data-driven Discovery for Accelerated Experimentation and Application
By Krishna Rajan
This work, from Krishna Rajan, the leading expert of the informatics approach to materials, seeks to break down the barriers between data management, quality standards, data mining, exchange, and storage and analysis, as a means of ...
Applied Data Science: Lessons Learned for the Data-Driven Business
By Martin Braschler, Thilo Stadelmann, Kurt Stockinger
This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at ...
Data-Driven Technology for Engineering Systems Health Management: Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions
By Gang Niu
This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the ...
Data-Driven Engineering Design
By Ang Liu, Yuchen Wang, Xingzhi Wang
This book addresses the emerging paradigm of data-driven engineering design.
Data-Driven Controller Design: The H2 Approach
By Alexandre Sanfelice Bazanella, Lucíola Campestrini, Diego Eckhard
As a matter of fact, the concepts in this book are being used, under the author’s supervision, for developing new software products in a automation company. The book will present simulation examples along the text.
Chemometrics: Data Driven Extraction for Science
By Richard G. Brereton
A new, full-color, completely updated edition of the key practical guide to chemometrics This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical ...