Theory and New Applications of Swarm Intelligence

201 Pages·7.36 MB·english

by  Parpinelli R.S.

THEORY AND

NEW APPLICATIONS
OF SWARM INTELLIGENCE

Edited by Rafael Parpinelli and Heitor S. Lopes
Theory and New Applications of Swarm Intelligence
Edited by Rafael Parpinelli and Heitor S. Lopes

Published by InTech
Janeza Trdine 9, 51000 Rijeka, Croatia

Copyright © 2012 InTech
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First published March, 2012
Printed in Croatia

A free online edition of this book is available at www.intechopen.com
Additional hard copies can be obtained from [email protected]

Theory and New Applications of Swarm Intelligence, Edited by Rafael Parpinelli
and Heitor S. Lopes
p. cm.
ISBN 978-953-51-0364-6

Contents

Preface IX
Chapter 1 Swarm-Based Metaheuristic
Algorithms and No-Free-Lunch Theorems 1
Xin-She Yang
Chapter 2 Analysis of the Performance of the Fish School
Search Algorithm Running in Graphic Processing Units 17
Anthony J. C. C. Lins, Carmelo J. A. Bastos-Filho,
Débora N. O. Nascimento, Marcos A. C.
Oliveira Junior and Fernando B. de Lima-Neto
Chapter 3 Social Emotional Optimization Algorithm
with Random Emotional Selection Strategy 33
Zhihua Cui, Yuechun Xu and Jianchao Zeng
Chapter 4 The Pursuit of Evolutionary Particle Swarm Optimization 51
Hong Zhang
Chapter 5 Volitive Clan PSO - An Approach for Dynamic
Optimization Combining Particle Swarm
Optimization and Fish School Search 69
George M. Cavalcanti-Júnior, Carmelo J. A.
Bastos-Filho and Fernando B. de Lima-Neto
Chapter 6 Inverse Analysis in Civil Engineering:
Applications to Identification of Parameters
and Design of Structural Material Using Mono
or Multi-Objective Particle Swarm Optimization 87
M. Fontan, A. Ndiaye, D. Breysse and P. Castéra
Chapter 7 Firefly Meta-Heuristic Algorithm for Training
the Radial Basis Function Network
for Data Classification and Disease Diagnosis 115
Ming-Huwi Horng, Yun-Xiang Lee,
Ming-Chi Lee and Ren-Jean Liou
VI Contents

Chapter 8 Under-Updated Particle Swarm
Optimization for Small Feature
Selection Subsets from Large-Scale Datasets 133
Victor Trevino and Emmanuel Martinez
Chapter 9 Predicting Corporate Forward 2 Month Earnings 163
Michael F. Korns

Preface

Swarm Intelligence is a research field that studies the emergent collective intelligence
of self-organized and decentralized simple agents. It is based on the social behavior
that can be observed in nature, such as in flocks of birds, fish schools and bee hives,
where a group of individuals with limited capabilities are able to emerge with
intelligent solutions for complex problems. Since long ago, researchers in Computer
Science have already realized the importance of emergent behaviors for complex
problem solving. This book gathers together some recent advances on Swarm
Intelligence, comprising new swarm-based optimization methods, hybrid algorithms
and innovative applications. The contents of this book allows the reader to get
acquainted with both theoretical and technical aspects and applications of Swarm
Intelligence.
I would like to thank the authors that made this book possible and Dr. Heitor Silvério
Lopes for all the help during the review process.

Dr. Rafael Stubs Parpinelli
Universidade do Estado de Santa Catarina (UDESC)
Brazil