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Artificial Neural Networks: an overview and their use in the analysis of the AMPHORA-3 dataset
Paolo Massimo Buscema1, Giulia Massini, Guido Maurelli
11Semeion Research Centre of Sciences of Communication Via Sersale 117 , Rome, 00128 , Italy.
Abstract:
The Artificial Adaptive Systems (AAS) are theories with which generative algebras are able to create artificial models simulating natural phenomenon. Artificial Neural Networks (ANNs) are the more diffused and best-known learning system models in the AAS. This article describes an overview of ANNs, noting its advantages and limitations for analyzing dynamic, complex, non-linear, multidimensional processes. An example of a specific ANN application to alcohol consumption in Spain, as part of the EU AMPHORA-3 project, during 1961-2006 is presented. Study's limitations are noted and future needed research using ANN methodologies are suggested.

