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In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.
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The Power of Geometric Algebra Computing for Engineering and Quantum Computing is based on GAALOPWeb, a new user-friendly,... Læs mere
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In this book the authors aim to endow the reader with an operational, conceptual, and methodological understanding of the discrete mathematics that can be used to study, understand, and perform computing.
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Metaheuristic Algorithms in Industry 4.0 provides a guiding light to engineers, researchers, students, faculty and other professionals engaged in exploring and implementing industry 4.0 solutions in various systems and processes.
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This book provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural... Læs mere
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‘Machine Learning for Knowledge Discovery with R’ contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes most recent supervised and unsupervised machine learning methodologies
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A conceptual introduction to the study of the intrinsic complexity of computational tasks. It will serve advanced undergraduate and graduate students,... Læs mere
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Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature... Læs mere
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Intended for graduate students and researchers, this book presents a formal development of the mathematical theory of quantum information. Largely self-contained, with... Læs mere
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This introductory book emphasizes algorithms and applications, and is accessible to a broad audience. The author alternates between theory and... Læs mere
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Introduces the universal-algebraic approach to the complexity classification of constraint satisfaction problems in the finite and infinite-domain... Læs mere
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Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed.