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2013 | OriginalPaper | Chapter

108. An Improved Discrete Particle Swarm Optimization Algorithm

Author : QingFeng Liu

Published in: Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012

Publisher: Springer London

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Abstract

Evolutionary algorithms solve complex identification problems because they do not take into account any constraint on the cost function and more flexibility is offered when the model structure is chosen and the cost function is minimized. Step input-based identification has been developed, which could be used to determine the transient behavior of a system rapidly. In this paper, a new discrete particle swarm optimization (DPSO) algorithm is presented and the performance of this algorithm for solving identification problems is compared with the GA. The obtained results demonstrate that the proposed DPSO algorithm performs rather well in terms of speed (FNGC) and reaching to the minimum cost.

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previous chapter A Delay-Constrained Multicast Routing Algorithm Based on the Ant Colony Algorithm
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Metadata
Title
An Improved Discrete Particle Swarm Optimization Algorithm
Author
QingFeng Liu
Copyright Year
2013
Publisher
Springer London
Book
Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012

Print ISBN: 978-1-4471-4852-4

Electronic ISBN: 978-1-4471-4853-1

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-1-4471-4853-1_108