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This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.

Engineering. --- Artificial intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Engineering & Applied Sciences --- Computer Science --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Construction --- Computational intelligence. --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Industrial arts --- Technology --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Artificial Intelligence.

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This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums, are presented. "Evolutionary Computation in Dynamic and Uncertain Environments" is a valuable reference for scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, natural computing and evolutionary computation.

Evolutionary computation. --- Réseaux neuronaux à structure évolutive --- Evolutionary computation --- Civil Engineering --- Computer Science --- Applied Mathematics --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Computation, Evolutionary --- Engineering. --- Artificial intelligence. --- Statistics. --- Applied mathematics. --- Engineering mathematics. --- Computational intelligence. --- Appl.Mathematics/Computational Methods of Engineering. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Intelligence, Computational --- Artificial intelligence --- Engineering --- Engineering analysis --- Mathematical analysis --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Soft computing --- Neural networks (Computer science) --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Statistics .

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The two-volume set IFIP AICT 703 and 704 constitutes the refereed conference proceedings of the 13th IFIP TC 12 International Conference on Intelligent Information Processing XII, IIP 2024, held in Shenzhen, China, during May 3–6, 2024. The 49 full papers and 5 short papers presented in these proceedings were carefully reviewed and selected from 58 submissions. The papers are organized in the following topical sections: Volume I: Machine Learning; Natural Language Processing; Neural and Evolutionary Computing; Recommendation and Social Computing; Business Intelligence and Risk Control; and Pattern Recognition. Volume II: Image Understanding.

Artificial intelligence. --- Artificial Intelligence.

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Artificial intelligence. Robotics. Simulation. Graphics --- AI (artificiële intelligentie)

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Statistical physics --- Engineering sciences. Technology --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- statistische kwaliteitscontrole --- analyse (wiskunde) --- industriële statistieken --- algoritmen --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- robots --- numerieke analyse