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Using the Kohonen Network to Group World Economies in the Context of Factors Characterizing the Meeting of their Energy Needs

Witold Roman
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Collegium of Economic Analysis Annals, 2017, issue 45, 347-358

Abstract: The purpose of the paper is clustering world economies in the context of factors characterizing the meeting of their energy needs. To achieve this purpose the Kohonen network was used, which realizes unsupervised learning (self-learning) network (SOM). The necessary computations were performed using the som () function of class package running in the R environment. The result of the clustering analysis was obtaining homogeneous groups of states worldwide. It can serve further elaborations over improving the meeting of Poland’s energy needs.

Keywords: artificial neural network; cluster; cluster analysis; meeting energy needs; R programming language; R software environment; self-organizing map (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:sgh:annals:i:45:y:2017:p:347-358