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Teaching particle swarm optimization through an open‐loop system identification project
Author(s) -
Oliveira Paulo Moura,
Vrančić Damir,
Cunha J. Boaventura,
Pires E. J. Solteiro
Publication year - 2014
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20549
Subject(s) - initialization , particle swarm optimization , computer science , identification (biology) , context (archaeology) , open loop controller , population , selection (genetic algorithm) , inertia , mathematical optimization , artificial intelligence , machine learning , engineering , control engineering , mathematics , closed loop , paleontology , botany , demography , physics , classical mechanics , sociology , biology , programming language
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. © 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:227–237, 2014; View this article online at wileyonlinelibrary.com/journal/cae ; DOI 10.1002/cae.20549