\u003cp\u003e\u003cb\u003eThorough review of how artificial intelligence can enhance the design, control, and optimization of power electronics systems\u003c/b\u003e \u003cp\u003e\u003ci\u003eArtificial Intelligence for Power Electronics\u003c/i\u003e 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\u0026A review sections, are included throughout the text, with coverage of both Python and MATLAB. \u003cp\u003eTopics discussed in \u003ci\u003eArtificial Intelligence for Power Electronics\u003c/i\u003e include: \u003cul\u003e\u003cli\u003eSupervised, unsupervised, and reinforcement machine learning and the role of data in training machine learning models\u003c/li\u003e\u003cli\u003eTechniques for AI data collection in power electronics and how to clean, normalize, and handle missing values of data\u003c/li\u003e\u003cli\u003eOptimization techniques such as Particle Swarm Optimization and Ant Colony Optimization\u003c/li\u003e\u003cli\u003eDetection techniques for identifying faults and anomalies and clustering algorithms to group similar operational behavior\u003c/li\u003e\u003cli\u003eEssential Python libraries for machine learning and how to perform machine learning on a Raspberry Pi\u003c/li\u003e\u003c/ul\u003e \u003cp\u003eDelivering an industry-specific approach to AI applications, \u003ci\u003eArtificial Intelligence for Power Electronics\u003c/i\u003e is a helpful reference for undergraduate, postgraduate, and PhD students in electrical, electronic, and computer engineering. Mechanical engineers and other industry professionals may also find it valuable.
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