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Neural Networks, Fuzzy Systems and Other Computational Intelligence Techniques for Advanced Process Control
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Computational intelligence (CI) techniques have developed very fast during the past two decades with many new methods emerging. Novel CI techniques, such as deep learning, convolutional neural networks, deep belief networks, long short-term memory networks, and reinforcement learning, have been successfully applied to solve many complicated problems ranging from image processing to natural language processing. These novel CI techniques have also been applied to the process systems engineering areas with many successful applications reported, such as data-driven modeling of nonlinear processes, inferential estimation and soft sensors, intelligent process monitoring, and process optimization based on CI techniques. This reprint contains 17 papers from a recent Special Issue of Processes on Neural Networks, Fuzzy Systems and Other Computational Intelligence Techniques for Advanced Process Control.
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