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Innovations in Swarm Intelligence

  • Book
  • © 2009

Overview

Editors:
  1. Chee Peng Lim

    1. University of South Australia, Adelaide, Australia

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  2. Lakhmi C. Jain

    1. University of South Australia, Adelaide, Australia

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  3. Satchidananda Dehuri

    1. Soft Computing Laboratory, Department of computer Science, Yonsei University, Seoul, Korea

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  • Latest research on the theory and applications of swarm intelligence for the design of knowledge-based systems

Part of the book series: Studies in Computational Intelligence (SCI, volume 248)

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Table of contents (12 chapters)

  1. Front Matter

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  2. Advances in Swarm Intelligence

    • Chee Peng Lim, Lakhmi C. Jain
    Pages 1-7

  3. A Review of Particle Swarm Optimization Methods Used for Multimodal Optimization

    • Julio Barrera, Carlos A. Coello Coello
    Pages 9-37

  4. Bee Colony Optimization (BCO)

    • DuÅ¡an Teodorović
    Pages 39-60

  5. Glowworm Swarm Optimization for Searching Higher Dimensional Spaces

    • K. N. Krishnanand, D. Ghose
    Pages 61-75

  6. Agent Specialization in Complex Social Swarms

    • Denton Cockburn, Ziad Kobti
    Pages 77-89

  7. Computational Complexity of Ant Colony Optimization and Its Hybridization with Local Search

    • Frank Neumann, Dirk Sudholt, Carsten Witt
    Pages 91-120

  8. A Multi-resolution GA-PSO Layered Encoding Cascade Optimization Model

    • Siew Chin Neoh, Norhashimah Morad, Arjuna Marzuki, Chee Peng Lim, Zalina Abdul Aziz
    Pages 121-140

  9. Integrating Swarm Intelligent Algorithms for Translation Initiation Sites Prediction

    • Jia Zeng, Reda Alhajj
    Pages 141-157

  10. Particle Swarm Optimization for Optimal Operational Planning of Energy Plants

    • Yoshikazu Fukuyama, Hideyuki Nishida, Yuji Todaka
    Pages 159-173

  11. Modelling Nanorobot Control Using Swarm Intelligence: A Pilot Study

    • Boonserm Kaewkamnerdpong, Peter J. Bentley
    Pages 175-214

  12. ACO Hybrid Algorithm for Document Classification System

    • Nikos Tsimboukakis, George Tambouratzis
    Pages 215-236

  13. Identifying Disease-Related Biomarkers by Studying Social Networks of Genes

    • Mohammed Alshalalfa, Ala Qabaja, Reda Alhajj, Jon Rokne
    Pages 237-253

  14. Back Matter

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Keywords

About this book

Over the past two decades, swarm intelligence has emerged as a powerful approach to solving optimization as well as other complex problems. Swarm intelligence models are inspired by social behaviours of simple agents interacting among themselves as well as with the environment, e.g., flocking of birds, schooling of fish, foraging of bees and ants. The collective behaviours that emerge out of the interactions at the colony level are useful in achieving complex goals.

The main aim of this research book is to present a sample of recent innovations and advances in techniques and applications of swarm intelligence. Among the topics covered in this book include: particle swarm optimization and hybrid methods, ant colony optimization and hybrid methods, bee colony optimization, glowworm swarm optimization, and complex social swarms, application of various swarm intelligence models to operational planning of energy plants, modeling and control of nanorobots, classification of documents, identification of disease biomarkers, and prediction of gene signals.

The book is directed to researchers, practicing professionals, and undergraduate as well as graduate students of all disciplines who are interested in enhancing their knowledge in techniques and applications of swarm intelligence.

Editors and Affiliations

  • University of South Australia, Adelaide, Australia

    Chee Peng Lim, Lakhmi C. Jain

  • Soft Computing Laboratory, Department of computer Science, Yonsei University, Seoul, Korea

    Satchidananda Dehuri

Bibliographic Information

  • Book Title: Innovations in Swarm Intelligence

  • Editors: Chee Peng Lim, Lakhmi C. Jain, Satchidananda Dehuri

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-04225-6

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2009

  • Hardcover ISBN: 978-3-642-04224-9Published: 28 September 2009

  • Softcover ISBN: 978-3-642-26056-8Published: 14 March 2012

  • eBook ISBN: 978-3-642-04225-6Published: 04 October 2009

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: VIII, 255

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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