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Artificial Intelligence for Power Electronics

Artificial Intelligence for Power Electronics | Ahteshamul Haque, Saad Mekhilef, Azra Malik
English | 2025 | True PDF, EPUB | 390 pages | 50.4 Mb
Artificial Intelligence for Power Electronics provides a comprehensive overview of the intersection between Artificial Intelligence (AI) and the field of power electronics, exploring how AI can revolutionize and enhance the design, control, and optimization of power electronics systems. The book covers the fundamentals of AI, the fundamentals of power electronics and the challenges the field faces in design to production, and the solutions of these challenges through AI methods. Example solutions, along with Q&A review sections, are included throughout the text, with coverage of both Python and MATLAB.
This book's purpose goes beyond simply teaching; it also seeks to ignite curiosity and foster exploration. Tools such as MATLAB/Simulink and Python are utilized to solve the power electronics–related problems using AI techniques.
The curriculum aims to stimulate students' interest, develop their analytical thinking, and motivate them to make significant contributions to this evolving field by showcasing real-world problems and presenting innovative solutions.
Contents:
Preface
1 Fundamentals of Power Electronics and Key Challenges
2 Introduction of AI and Utility for Power Electronics Applications
3 Machine Learning Fundamentals
4 Data Collection and Pre-processing
5 Fuzzy Logic and Metaheuristic Methods in Power Electronics
6 Supervised Learning for Power Electronics
7 Unsupervised Learning for Anomaly Detection
8 Reinforcement Learning and Control
9 Implementation of Machine Learning for Power Electronics Application Using MATLAB
10 Implementation of Machine Learning for Power Electronics Application Using PYTHON
11 Integration of AI in Power Electronics in Real-time
Index
1 Fundamentals of Power Electronics and Key Challenges
2 Introduction of AI and Utility for Power Electronics Applications
3 Machine Learning Fundamentals
4 Data Collection and Pre-processing
5 Fuzzy Logic and Metaheuristic Methods in Power Electronics
6 Supervised Learning for Power Electronics
7 Unsupervised Learning for Anomaly Detection
8 Reinforcement Learning and Control
9 Implementation of Machine Learning for Power Electronics Application Using MATLAB
10 Implementation of Machine Learning for Power Electronics Application Using PYTHON
11 Integration of AI in Power Electronics in Real-time
Index
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