Using the Kohonen Network to Group World Economies in the Context of Factors Characterizing the Meeting of their Energy Needs
Additional contact information
Witold Roman: NULL
Collegium of Economic Analysis Annals, 2017, issue 45, 347-358
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)
References: Add references at CitEc
Citations Track citations by RSS feed
Downloads: (external link)
http://rocznikikae.sgh.waw.pl/p/roczniki_kae_z45_25.pdf Full text (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:sgh:annals:i:45:y:2017:p:347-358
Access Statistics for this article
Collegium of Economic Analysis Annals is currently edited by Joanna Plebaniak, Beata Czarnacka-Chrobot
More articles in Collegium of Economic Analysis Annals from Warsaw School of Economics, Collegium of Economic Analysis Contact information at EDIRC.
Series data maintained by Michał Bernardelli ().