Neural Network add-in for PSORT

This add-in allows a Neural Network to be trained by Particle Swarm Optimization technique.
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Actualizado 11 ene 2011

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This add-in to the PSO Research toolbox (Evers 2009) aims to allow an artificial neural network (ANN or simply NN) to be trained using the Particle Swarm Optimization (PSO) technique (Kennedy, Eberhart et al. 2001).

This add-in acts like a bridge or interface between MATLAB’s NN toolbox and the PSO Research Toolbox. In this way, MATLAB’s NN functions can call the NN add-in, which in turn calls the PSO Research toolbox for NN training.

This approach to training a NN by PSO treats each PSO particle as one possible solution of weight and bias combinations for the NN (Settles and Rylander ; Rui Mendes 2002; Venayagamoorthy 2003). The PSO particles therefore move about in the search space aiming to minimise the output of the NN performance function.

The author acknowledges that there already exists code for PSO training of a NN (Birge 2005), however that code was found to work only with MATLAB version 2005 and older. This NN-addin works with newer versions of MATLAB till versions 2010a.

1. This NN add-in only works when used with the PSORT found at,

2. The author acknowledges the modification of code used in an old PSO toolbox for NN training found at

3. User support and contact information for the author of this NN add-in can be found at

The author acknowledges the support of advisors and fellow researchers who supported in various ways to better her understanding of PSO and NN which lead to the creation of this add-in for PSO training of NNs. The acknowledged are as follows:
* Dr. Alexander Nikov - Senior lecturer and Head of Usaility Lab, UWI, St. Augustine, Trinidad, W.I.
* Dr. Sabine Graf - Assistant Professor, Athabasca University, Alberta, Canada.
* Dr. Kinshuk - Professor, Athabasca University, Alberta, Canada.
* Members of the iCore group at Athabasca University, Edmonton, Alberta, Canada.

Citar como

Tricia Rambharose (2024). Neural Network add-in for PSORT (, MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2010a
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Versión Publicado Notas de la versión

Updated job titles of Acknowledged professors.

Updates made to include an acknowledgements section of the description.