Data driven analysis modeling (18 Ergebnisse)

paperback. Zustand: Good. spine has cut in it.

paperback. Zustand: Very Good. Cover and edges may have some wear.

paperback. Zustand: Fine.

Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New. 2021. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Modeling and Analysis of Actual Evapotranspiration | Data Driven Modeling and Wavelet Analysis of Actual Evapotranspiration | Zohreh Izadifar (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639291612 | Verantwortliche Person für die EU: VDM Verlag Dr. Müller, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.…

Zustand: New. In.

Paperback. Zustand: Brand New. 252 pages. 9.25x6.10x0.60 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.…

Taschenbuch. Zustand: Neu. Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis | Sujit Rokka Chhetri (u. a.) | Taschenbuch | xvi | Englisch | 2021 | Springer | EAN 9783030379643 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Hardcover. Zustand: Brand New. 252 pages. 9.25x6.10x0.87 inches. In Stock.

Zustand: New.

Zustand: New. In.

Zustand: New. Redaktion: Karthik DuraisamyKarthik Duraisamy is a professor of Aerospace Engineering and the director of the Michigan Institute for Computational Discovery at the University of Michigan, Ann Arbor, USA. His research interests are in data-driven .

Taschenbuch. Zustand: Neu. Neuware - Data-driven Analysis and Modeling of Turbulent Flows provides an integrated treatment of modern data-driven methods to describe, control, and predict turbulent flows through the lens of both physics and data science.The book is organized into three parts:Exploration of techniques for discovering coherent structures within turbulent flows, introducing advanced decomposition methodsMethods for estimation and control using data assimilation and machine learning approachesFinally, novel modeling techniques that combine physical insights with machine learningThis book is intended for students, researchers, and practitioners in fluid mechanics, though readers from related fields such as applied mathematics, computational science, and machine learning will find it also of interest.…