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Full Description
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, transforming information into knowledge.
Drawing on the authors' teaching experience, the book takes a practical approach to applying artificial intelligence tools - such as regression, classification, clustering, deep learning and reinforcement learning- to real-world engineering problems. Through clear explanations and step-by-step algorithmic structures, readers are introduced to the fundamental concepts of artificial intelligence and their practical application by building AI models using automotive data. Examples include predicting the energy consumption of electric vehicles under varying environmental and operating conditions, assessing battery degradation, analyzing brake system wear, and implementing intelligent control for thermal management (HVAC systems). The book shows how the application of artificial intelligence techniques and methods can optimize performance, increase safety, and stimulate innovation in the automotive sector.
The book represents an essential guide for all those interested in exploring the application of artificial intelligence in automotive engineering (and beyond) and equally constitutes an effective support in the teaching process (courses, laboratories, projects) of applied artificial intelligence concepts.
Contents
Foreword
1. Introduction to Artificial Intelligence
2. Regression methods
3. Classification tools
4. Decision Trees method
5. K-means and hierarchical clustering
6. Support Vector Machine method
7. Neural networks
