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Inspired by the structure of the human brain, artificial neural networks have found many applications due to their ability to solve cumbersome or intractable problems by learning from data. Neural networks can adapt to new environments by learning, and deal with information that is noisy. inconsistent, vague, or probabilistic. This volume of Neural Network Systems Techniques and Applications is devoted to Optimization Techniques, including systems structures and computional methods.
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Practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering will find this volume a unique reference to a diverse array of methods for achieving optimization.
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