Exploratory analysis of computational social simulation outputs by multivariate statistics and self-organizing maps
DOI:
https://doi.org/10.14808/sci.plena.2016.071301Keywords:
socioterritorial system, artificial neural network, social theoryAbstract
This work aimed at the application of principal component analysis, clustering by the agglomerative hierarchical method and the Kohonen Self-Organizing Map neural network in the exploratory analysis of social simulation outputs of the socioterritorial system " Southern Rural Territory of Sergipe ". The method is based on the Sociology of Organized Action and on the Soclab framework. The analysis showed that these outputs confirmed the tendency of the socioterritoial system towards stability. However, it was observed by the neural network that there are differences, though small, among the situations that lead to the steadyness of the system.
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Published
2016-07-20
How to Cite
Santos da Silva, M. A., Santos, A. V., Galina, M. H., Medeiros, S. dos S., & de Almeida, M. R. M. (2016). Exploratory analysis of computational social simulation outputs by multivariate statistics and self-organizing maps. Scientia Plena, 12(7). https://doi.org/10.14808/sci.plena.2016.071301
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