Innovations in Swarm Intelligence

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 bir...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Lim, Chee Peng (Επιμελητής έκδοσης), Jain, Lakhmi C. (Επιμελητής έκδοσης), Dehuri, Satchidananda (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
Σειρά:Studies in Computational Intelligence, 248
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Innovations in Swarm Intelligence  |h [electronic resource] /  |c edited by Chee Peng Lim, Lakhmi C. Jain, Satchidananda Dehuri. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2009. 
300 |a VIII, 255 p.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 248 
505 0 |a 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. 
520 |a 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, modelling 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. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
650 1 4 |a Engineering. 
650 2 4 |a Appl.Mathematics/Computational Methods of Engineering. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Lim, Chee Peng.  |e editor. 
700 1 |a Jain, Lakhmi C.  |e editor. 
700 1 |a Dehuri, Satchidananda.  |e editor. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783642042249 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 248 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-04225-6  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)