Dr Noura Al Moubayed noura.al-moubayed@durham.ac.uk
Associate Professor
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
Authors
B Awwad Shiekh Hasan
JQ Gan
A Petrovski
J McCall
Abstract
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).
Presentation Conference Type | Conference Paper (Published) |
---|---|
Conference Name | 2010 UK Workshop on Computational Intelligence (UKCI) |
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 |
DOI | https://doi.org/10.1109/ukci.2010.5625570 |
Public URL | https://durham-repository.worktribe.com/output/1151921 |
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