Self-Organizing Maps
Analysis of Parliamentary Election Results and Socio-Economic Situation Using Self-Organizing Map
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Topology preservation in self-organizing feature maps: exact definition and measurement
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using the self-organizing map
IEEE Transactions on Neural Networks
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
Hi-index | 0.00 |
We propose the use of self-organizing maps as models of social processes, in particular, of electoral preferences. In some voting districts patterns of electoral preferences emerge, such that in nearby areas citizens tend to vote for the same candidate whereas in geographically distant areas the most voted candidate is that whose political position is distant to the latter. Those patterns are similar to the spatial structure achieved by self-organizing maps. This model is able to achieve spatial order from disorder by forming a topographic map of the external field, identified with advertising from the media. Here individuals are represented in two spaces: a static geographical location, and a dynamic political position. The modification of the later leads to a pattern in which both spaces are correlated.