Biogeography-Based Optimization: Algorithms and Applications (PDF)
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This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.
Dr. Xueqin Lu is a Ph.D. candidate at College of Computer Science and Technology, Zhejiang University of Technology, China. Her main research interests are bio-inspired algorithms and their applications.
Dr. Minxia Zhang is an Associate Professor at College of Computer Science and Technology, Zhejiang University of Technology, China. Her main research interests include bio-inspired computation and its applications.
Dr. Shengyong Chen received his Ph.D. degree from City University of Hong Kong in 2003, and now is Professor, Director of Institute of Computer Vision, at College of Computer Science and Technology, Zhejiang University of Technology, China. His research focuses on computer vision and robotics. Prof. Chen is a recipient of National Outstanding Youth Foundation Award (NSFC) in 2014, IEEE Sensors Journal Best Paper Award in 2012, Research Fellowship of Alexander von Humboldt, Germany in 2006 and is also IET fellow, IEEE senior member.
- Autoren: Yujun Zheng , Xueqin Lu , Minxia Zhang , Shengyong Chen
- 2018, 1st ed. 2019, 221 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811325863
- ISBN-13: 9789811325861
- Erscheinungsdatum: 14.09.2018
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- Dateiformat: PDF
- Größe: 7.35 MB
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