Please use this identifier to cite or link to this item:

Title: A Self-Organizing Map of the Elections in Portugal
Authors: Caleiro, António
Keywords: Elections
Electoral Business Cycles
Neural Networks
Self-Organizing Maps
Issue Date: Apr-2013
Citation: Caleiro, António (2013), "A Self-Organizing Map of the Elections in Portugal", The IIOAB Journal , Special Issue (Neuroscience in Economic Decision Making), 4: 3, April-June, 9-14.
Abstract: As (artificial) neural networks are simulations of the supposed biological neurons work, the structure of human brains - where processing units, the so-called neurons, are connected by synapses - is approximated by (artificial) neural networks. As most of neural networks, self-organizing maps are trained through a learning process. By the use of a neighborhood function in this learning process, self- organizing maps (SOMs) thus allow to visualize which (and how) democratic elections were more similar/distinct. For Portugal the SOM identifies two clusters of elections: one made of those corresponding to a re-election of the incumbent, i.e. in 1987, 1995, 1999 and 2009; and another made of elections that led to a change in the party in power, i.e. 1991, 2002, 2005 and 2011.
Type: article
Appears in Collections:ECN - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

Files in This Item:

File Description SizeFormat
Caleiro_2013b.pdf112.53 kBAdobe PDFView/OpenRestrict Access. You can Request a copy!
FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpaceOrkut
Formato BibTex mendeley Endnote Logotipo do DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Dspace Dspace
DSpace Software, version 1.6.2 Copyright © 2002-2008 MIT and Hewlett-Packard - Feedback
UEvora B-On Curriculum DeGois