Fractional Order Darwinian Particle Swarm Optimization Applications
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
- PDF / 5,263,314 Bytes
- 82 Pages / 439.37 x 666.142 pts Page_size
- 42 Downloads / 245 Views
Micael Couceiro Pedram Ghamisi
Fractional Order Darwinian Particle Swarm Optimization Applications and Evaluation of an Evolutionary Algorithm 123
SpringerBriefs in Applied Sciences and Technology
More informations about this series at http://www.springer.com/series/8884
Micael Couceiro Pedram Ghamisi •
Fractional Order Darwinian Particle Swarm Optimization Applications and Evaluation of an Evolutionary Algorithm
123
Micael Couceiro Ingeniarius, Ltd. Mealhada Portugal and
Pedram Ghamisi Faculty of Electrical and Computer Engineering University of Iceland Reykjavik Iceland
Institute of Systems and Robotics (ISR) University of Coimbra Coimbra Portugal
ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISBN 978-3-319-19634-3 ISBN 978-3-319-19635-0 (eBook) DOI 10.1007/978-3-319-19635-0 Library of Congress Control Number: 2015940427 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
Foreword
Biomimetics has been exploited in several research areas as a means to endow artificial systems with intelligence, resilience, adaptation, and natural selection typically exhibited by living organisms and biological ecosystems, in order to solve complex human problems through new technologies inspired by such biological systems at macro-and nanoscales. Bioinspiration has received special attention in the robotics community for the past two decades in order to solve complex optimization problems through bioinspired algorithms. It has been mainly devoted to the study of robot swarms comprising many unsophisticated robots interacting locally with neighbor robots and the environment, which can exhibit useful collective patterns resembling the way swarms of biological species behave collectively to strive for survival in hostile environment
Data Loading...
