Application of clustering methods for optimizing the location of treated wood remediation units.

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Abstract

In this paper we used two clustering methods (SOM and K-means) to optimize the location of CCA (Chromated Copper Arsenate)-treated wood waste remediation units in Portugal. We used the SOM Toolbox for Matlab implementation with the population data from the last census made by the National Statistics Institute. The two methods yield good results, but we concluded that the k-means algorithm provided better solutions than the SOM in this particular problem.
Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalRevista da Associação Portuguesa de Classificação e Análise de Dados
Volume8
Issue numberNA
Publication statusPublished - 1 Jan 2011

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