| 书目名称 | Fractional Order Darwinian Particle Swarm Optimization |
| 副标题 | Applications and Eva |
| 编辑 | Micael Couceiro,Pedram Ghamisi |
| 视频video | http://file.papertrans.cn/348/347408/347408.mp4 |
| 概述 | Contributes to the state-of-the-art on the use of swarm intelligence to solve real-world problems.Compares the capabilities of various bio-inspired optimization approaches.Demonstrates the superiority |
| 丛书名称 | SpringerBriefs in Applied Sciences and Technology |
| 图书封面 |  |
| 描述 | .This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, such as its ability to provide an improved convergence towards a solution, while avoiding sub-optimality. This book offers a valuable resource for researchers in the fields of robotics, sports science, pattern recognition and machine learning, as well as for students of electrical engineering and computer science.. |
| 出版日期 | Book 2016 |
| 关键词 | Advantages of FODPSO; Bio-inspired optimization approaches; Bottom-up applicability of swarm intellige |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-19635-0 |
| isbn_softcover | 978-3-319-19634-3 |
| isbn_ebook | 978-3-319-19635-0Series ISSN 2191-530X Series E-ISSN 2191-5318 |
| issn_series | 2191-530X |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
|Archiver|手机版|小黑屋|
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