Artificial Intelligence in Manufacturing Concepts and Methods
Coordonnateurs : Soroush Masoud, D Braatz Richard
Artificial Intelligence in Manufacturing: Concepts and Methods explains the most successful emerging techniques for applying AI to engineering problems. Artificial intelligence is increasingly being applied to all engineering disciplines, producing more insights into how we understand the world and allowing us to create products in new ways. This book unlocks the advantages of this technology for manufacturing by drawing on work by leading researchers who have successfully developed methods that can apply to a range of engineering applications.
The book addresses educational challenges needed for widespread implementation of AI and also provides detailed technical instructions for the implementation of AI methods. Drawing on research in computer science, physics and a range of engineering disciplines, this book tackles the interdisciplinary challenges of the subject to introduce new thinking to important manufacturing problems.
2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge
3. Dynamical Systems-Guided Learning of PDEs from Data
4. Learning First-principles Knowledge from Data
5. Actual Learning through Machine Learning
6. Iterative Cross Learning
7. Learning an Algebraic Model from Data
8. Data-driven Optimization Algorithms
9. Interpretable Machine Learning
10. Learning Science and Algorithms
11. Reinforcement Learning
12. Machine Learning: Trends, Perspectives, and Prospects
13. Artificial Intelligence: Trends, Perspectives, and Prospects
14. Artificial Intelligence Education for Chemical Engineers
Richard D Braatz works in the Department of Chemical Engineering at Massachusetts Institute of Technology, Cambridge, USA.
- Presents AI concepts from the computer science field using language and examples designed to inspire engineering graduates
- Provides worked examples throughout to help readers fully engage with the methods described
- Includes concepts that are supported by definitions for key terms and chapter summaries
Date de parution : 01-2024
Ouvrage de 372 p.
15.2x22.8 cm