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Sprache: Englisch
Verlag: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041237227 ISBN 13: 9781041237228
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
EUR 69,04
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In den WarenkorbPaperback. Zustand: new. Paperback. This book serves as a timely and practical guide to understanding how artificial intelligence (AI) can be harnessed in automotive engineering. It not only demystifies complex AI methods but also equips readers with the tools to creatively apply them to their own engineering challenges. Drawing from the authors' extensive teaching experience, this book adopts a hands-on approach to applying AI tools such as regression, classification, clustering, and deep learning (DL) to real-world engineering challenges. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the foundational AI concepts and guided through practical applications using real automotive data. Examples include predicting electric vehicle energy consumption under varying conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). This book demonstrates how AI can optimize performance, enhance safety and drive innovation. Each chapter builds essential skills, including setting up machine learning (ML) environments, implementing regression and classification models, constructing decision trees, applying clustering techniques, and designing neural networks (NNs). This guide is essential for postgraduate students interested in exploring how AI can be applied in engineering. This book serves as a practical and timely guide to understanding how artificial intelligence can be applied and leveraged in automotive engineering. It demystifies complex methods of applying artificial intelligence and provides readers with the tools to creatively and immediately apply them to their own engineering challenges. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Anbieter: moluna, Greven, Deutschland
Zustand: New. Thomas Imre Cyrille Buidin is assistant professor in the Department of Automotive Engineering and Transports at the Technical University of Cluj-Napoca (UTCN), and a member of the Electric Mobility Applied Research Center (EMARC) research group. H.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Jun 2026, 2026
ISBN 10: 1041237227 ISBN 13: 9781041237228
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This book serves as a timely and practical guide to understanding how artificial intelligence (AI) can be harnessed in automotive engineering. It not only demystifies complex AI methods but also equips readers with the tools to creatively apply them to their own engineering challenges. Drawing from the authors' extensive teaching experience, this book adopts a hands-on approach to applying AI tools - such as regression, classification, clustering, and deep learning (DL) - to real-world engineering challenges. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the foundational AI concepts and guided through practical applications using real automotive data. Examples include predicting electric vehicle energy consumption under varying conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). This book demonstrates how AI can optimize performance, enhance safety and drive innovation. Each chapter builds essential skills, including setting up machine learning (ML) environments, implementing regression and classification models, constructing decision trees, applying clustering techniques, and designing neural networks (NNs). This guide is essential for postgraduate students interested in exploring how AI can be applied in engineering.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041237227 ISBN 13: 9781041237228
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Paperback. Zustand: new. Paperback. This book serves as a timely and practical guide to understanding how artificial intelligence (AI) can be harnessed in automotive engineering. It not only demystifies complex AI methods but also equips readers with the tools to creatively apply them to their own engineering challenges. Drawing from the authors' extensive teaching experience, this book adopts a hands-on approach to applying AI tools such as regression, classification, clustering, and deep learning (DL) to real-world engineering challenges. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the foundational AI concepts and guided through practical applications using real automotive data. Examples include predicting electric vehicle energy consumption under varying conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). This book demonstrates how AI can optimize performance, enhance safety and drive innovation. Each chapter builds essential skills, including setting up machine learning (ML) environments, implementing regression and classification models, constructing decision trees, applying clustering techniques, and designing neural networks (NNs). This guide is essential for postgraduate students interested in exploring how AI can be applied in engineering. This book serves as a practical and timely guide to understanding how artificial intelligence can be applied and leveraged in automotive engineering. It demystifies complex methods of applying artificial intelligence and provides readers with the tools to creatively and immediately apply them to their own engineering challenges. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041237227 ISBN 13: 9781041237228
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: new. Paperback. This book serves as a timely and practical guide to understanding how artificial intelligence (AI) can be harnessed in automotive engineering. It not only demystifies complex AI methods but also equips readers with the tools to creatively apply them to their own engineering challenges. Drawing from the authors' extensive teaching experience, this book adopts a hands-on approach to applying AI tools such as regression, classification, clustering, and deep learning (DL) to real-world engineering challenges. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the foundational AI concepts and guided through practical applications using real automotive data. Examples include predicting electric vehicle energy consumption under varying conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). This book demonstrates how AI can optimize performance, enhance safety and drive innovation. Each chapter builds essential skills, including setting up machine learning (ML) environments, implementing regression and classification models, constructing decision trees, applying clustering techniques, and designing neural networks (NNs). This guide is essential for postgraduate students interested in exploring how AI can be applied in engineering. This book serves as a practical and timely guide to understanding how artificial intelligence can be applied and leveraged in automotive engineering. It demystifies complex methods of applying artificial intelligence and provides readers with the tools to creatively and immediately apply them to their own engineering challenges. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
EUR 86,24
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In den WarenkorbZustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.