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.
eBook - ePub
Introduction to Artificial Intelligence in Automotive Engineering
Understanding Theory and Practical Applications
- 286 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Introduction to Artificial Intelligence in Automotive Engineering
Understanding Theory and Practical Applications
About this book
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Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- Introduction: AI and Automotive Engineering
- About the Authors
- Chapter 1 ◾ Introduction to Artificial Intelligence
- Chapter 2 ◾ Regression Methods
- Chapter 3 ◾ Classification Tools
- Chapter 4 ◾ Decision Trees Method
- Chapter 5 ◾ K-means and Hierarchical Clustering
- Chapter 6 ◾ Support Vector Machine Method
- Chapter 7 ◾ Neural Networks
- Chapter 8 ◾ Reinforcement Learning
- Index
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Yes, you can access Introduction to Artificial Intelligence in Automotive Engineering by Thomas Imre Cyrille Buidin,Florin Emil Mariasiu in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.