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£ 28.70
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Genetic Programming : 21st European Conference, Eurogp 2018, Parma, Italy, April 4-6, 2018, Proceedings
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Simulated Evolution and Learning: 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings (Lecture Notes in Computer Science, 8886)
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£ 51.28
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Electrospun Fibers Membranes for Oil-Water Emulsion Separation
Published by LAP LAMBERT Academic Publishing, 2018
ISBN 10: 6138321561 ISBN 13: 9786138321569
Language: English
£ 47.30
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Genetic Programming for Production Scheduling : An Evolutionary Learning Approach
Published by Springer Nature Singapore, 2022
ISBN 10: 9811648611 ISBN 13: 9789811648618
Language: English
£ 72.80
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Add to basketCondition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
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Simulated Evolution and Learning: 11th International Conference, SEAL 2017, Shenzhen, China, November 10-13, 2017, Proceedings (Lecture Notes in Computer Science, 10593)
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Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances
Published by Springer International Publishing, 2022
ISBN 10: 3031168674 ISBN 13: 9783031168673
Language: English
£ 107.78
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Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances (Studies in Computational Intelligence)
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Handbook of Evolutionary Machine Learning
Published by Springer Nature Singapore, 2023
ISBN 10: 9819938139 ISBN 13: 9789819938131
Language: English
£ 113.05
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Genetic Programming for Production Scheduling : An Evolutionary Learning Approach
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Big Data Analytics in Healthcare
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Genetic Programming for Image Classification: An Automated Approach to Feature Learning (Adaptation, Learning, and Optimization)
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Frosting and Icing for Efficient Energy Use in Engineering Applications (Paperback)
Published by Elsevier - Health Sciences Division, Philadelphia, 2025
ISBN 10: 0443154953 ISBN 13: 9780443154959
Language: English
Paperback. Condition: new. Paperback. Frosting and Icing for Efficient Energy Use in Engineering Applications provides a compendium of innovative case studies for mitigating impacts from frosting and icing on energy. This book first clarifies the mechanisms of frosting and icing, outlining modeling options, and control techniques. Next, a series of experimental examples show the effects of frosting at different scales of energy production, from ambient air vaporizers to wind turbines, and demonstrate how to control these for maximum efficiency. Finally, the mechanisms and mitigation of frosting are examined in a variety of infrastructure scenarios, including sustainable food storage and efficient high-speed railways.Combining the theoretical fundamentals of frosting and icing with a huge range of real-world case studies, this resource shows how to limit energy loss to these effects in key areas of engineering. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Big Data Analytics in Healthcare
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Genetic Programming for Image Classification: An Automated Approach to Feature Learning (Adaptation, Learning, and Optimization, 24)
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Condition: New.
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Handbook of Evolutionary Machine Learning
Published by Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10: 9819938163 ISBN 13: 9789819938162
Language: English
£ 224.56
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains.This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning.
