Title
Teaching particle swarm optimization through an open-loop system identification project
Abstract
The particle swarm optimization (PSO), one of the most successful natural inspired algorithms, is revisited in the context of a proposal for a new teaching experiment. The problem considered is the open-loop step identification procedure, which is studied as an optimization problem. The PSO canonical algorithm main issues addressed within the proposed open-loop step identification experience are: the swarm random initialization methodology, the population size variation, and the inertia weight selection. The teaching experience learning outcomes are stated, simulation results presented, and feedback results from students analyzed. (c) 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:227-237, 2014; View this article online at ; DOI
Year
DOI
Venue
2014
10.1002/cae.20549
Computer Applications in Engineering Education
Keywords
Field
DocType
particle swarm optimization
Particle swarm optimization,Mathematical optimization,Swarm behaviour,Computer science,Simulation,Multi-swarm optimization,Artificial intelligence,Inertia,Initialization,Open-loop controller,Optimization problem,Metaheuristic
Journal
Volume
Issue
ISSN
22
2
1061-3773
Citations 
PageRank 
References 
3
0.52
5
Authors
4
Name
Order
Citations
PageRank
Paulo B. de Moura Oliveira1309.66
Damir Vrancic2234.55
J. Boaventura Cunha3258.22
E. J. Solteiro Pires48113.95