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Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces

Al Moubayed, N; Awwad Shiekh Hasan, B; Gan, JQ; Petrovski, A; McCall, J


B Awwad Shiekh Hasan

JQ Gan

A Petrovski

J McCall


In, we introduced Smart Multi-Objective Particle Swarm Optimisation using Decomposition (SDMOPSO). The method uses the decomposition approach proposed in Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D), whereby a multi-objective problem (MOP) is represented as several scalar aggregation problems. The scalar aggregation problems are viewed as particles in a swarm; each particle assigns weights to every optimisation objective. The problem is solved then as a Multi-Objective Particle Swarm Optimisation (MOPSO), in which every particle uses information from a set of defined neighbours. This work customize SDMOSPO to cover binary problems and applies the proposed binary method on the channel selection problem for Brain-Computer Interfaces (BCI).


Al Moubayed, N., Awwad Shiekh Hasan, B., Gan, J., Petrovski, A., & McCall, J. (2010). Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces. .

Conference Name 2010 UK Workshop on Computational Intelligence (UKCI)
Conference Location Colchester, UK
Start Date Sep 8, 2010
End Date Sep 10, 2010
Online Publication Date Nov 9, 2020
Publication Date 2010
Deposit Date Jan 26, 2016
Publisher Institute of Electrical and Electronics Engineers
Pages 1-6
Series ISSN 2162-7657
ISBN 978-1-4244-8774-5
Public URL