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

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).

Citation

Al Moubayed, N., Awwad Shiekh Hasan, B., Gan, J., Petrovski, A., & McCall, J. (2010, September). Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces. Presented at 2010 UK Workshop on Computational Intelligence (UKCI), Colchester, UK

• 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