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Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system behavior. Fuzzy systems have similar applications. Their main advantage is their simplicity and ease of implementation. Various aspects of neural networks and fuzzy systems are covered in this volume from The Industrial Electronics Handbook, Second Edition. System optimization is also examined and several new techniques are discussed, including evolutionary methods and swarm and ant colony optimizations. The last section is devoted to several applications involving methods of computational intelligence.