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Enhanced self organizing map (ESOM) and particle swarm optimization (PSO) for classification

Hasan, Shafaatunnur and Shamsuddin, Siti Mariyam and Yusob, Bariah (2009) Enhanced self organizing map (ESOM) and particle swarm optimization (PSO) for classification. In: Konferensi Nasional Teknologi Informasi dan Aplikasinya, 2009, Palembang, Indonesia.

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Abstract

Hybrid technique for Self Organizing Map and Particle Swarm Optimization approach is commonly implemented in clustering area. In this paper, a hybrid approach that is based on Enhanced Self Organizing Map and Particle Swarm Optimization (ESOM/PSO) for classification is proposed. Enhanced Self Organization map which based on Kohonen network structure is to improve the quality of the data classification and labeling. New formulation of hexagonal lattice area is used for the enhancement Self Organizing Map structure. The proposed hybrid ESOM/PSO algorithm uses PSO to evolve the weights for ESOM. The weights are trained by ESOM in the first stage. In the second stage, they are optimized by PSO.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Enhanced Self Organizing Map (SOM), Particle Swarm Optimization (PSO), classification
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:15152
Deposited By: Narimah Nawil
Deposited On:21 Sep 2011 09:46
Last Modified:20 Jul 2020 01:24

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