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Bioinspired optimization methods and their applications ; 9th International conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings

This book constitutes the refereed proceedings of the 9th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2020, held in Brussels, Belgium, in November 2020. The 24 full papers presented in this book were carefully reviewed and selected from 68 submissions. The papers in this BIOMA proceedings specialized in bioinspired algorithms as a means for solving the optimization problems and came in two categories: theoretical studies and methodology advancements on the one hand, and algorithm adjustments and their applications on the other.

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Artificial immune systems ; 7th International Conference, ICARIS 2008, Phuket, Thailand, August 10-13, 2008. Proceedings

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Immune Systems, ICARIS 2008, held in Phuket, Thailand, in August 2008.

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Artificial immune systems ; 6th International Conference, ICARIS 2007, Santos, Brazil, August 26-29, 2007, Proceedings

This book contains sections on search and optimization, classification and clustering, anomaly detection and negative selection, robotics, control and electronics. Modeling papers, conceptual papers, and technical papers and general applications are also included.

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Advances in Structural Engineering - Optimization : Emerging Trends in Structural Optimization

An up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches.

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