Innovations in swarm intelligence
Author(s)
Bibliographic Information
Innovations in swarm intelligence
(Studies in computational intelligence, v. 248)
Springer, c2010
- : softcover
Available at 1 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
"Softcover reprint of the hardcover 1st edition 2010"--T.p. verso
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
Advances in Swarm Intelligence.- A Review of Particle Swarm Optimization Methods Used for Multimodal Optimization.- Bee Colony Optimization (BCO).- Glowworm Swarm Optimization for Searching Higher Dimensional Spaces.- Agent Specialization in Complex Social Swarms.- Computational Complexity of Ant Colony Optimization and Its Hybridization with Local Search.- A Multi-resolution GA-PSO Layered Encoding Cascade Optimization Model.- Integrating Swarm Intelligent Algorithms for Translation Initiation Sites Prediction.- Particle Swarm Optimization for Optimal Operational Planning of Energy Plants.- Modelling Nanorobot Control Using Swarm Intelligence: A Pilot Study.- ACO Hybrid Algorithm for Document Classification System.- Identifying Disease-Related Biomarkers by Studying Social Networks of Genes.
by "Nielsen BookData"