Artificial Neural Networks: An Overview and their Use in the Analysis of the AMPHORA-3 Dataset. (15th October 2014)

• Record Type: Journal Article
• Authors: Buscema, Paolo Massimo; Massini, Giulia; Maurelli, Guido
• Is Part Of: Substance use & misuse. Volume 49:Number 12(2014)
• Page Start: 1555
• Page End: 1568
• Publication Date: 2014-10-15
• Subjects: artificial neural networks -- artificial adaptive systems -- supervised and unsupervised ANNs; Narcotic habit -- Periodicals; Alcoholism -- Periodicals; Substance abuse -- Periodicals; Behavior, Addictive -- Periodicals; Sustance-Related Disorders -- Periodicals; 362.2905
• DOI: 10.3109/10826084.2014.933009
• Languages: English
• ISSNs: 1082-6084

Abstract

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.