First, it provides an overview of artificial intelligence, of its paradigms (machine learning, search methods, logic-based tools, knowledge-based tools, and probabilistic methods), and the types of problems AI addresses: classification, regression, optimization, and prediction. Second, it presents techniques such as artificial neural network and deep learning, evolution theory-inspired algorithms, fuzzy sets, and rough sets. Third, it explains how these techniques could cope with some power electronics problems, in order to give the audience a glance at potential research opportunities regarding the applying of AI in power electronics. Fourth, it presents a variety of applications of these techniques for different power electronics problems, ranging from optimum design, control, reliability, energy management, to smart grid, and examines successfully implemented examples. Finally, it highlights AI research trends and possible future applications to power electronics.
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