by Nastac, Iulian;
Bacivarov, Angelica and Costea, Adrian
Published in Romanian Journal of Economic Forecasting, 2009, volume 11 issue 3, 100-109
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This paper presents an original classifier model based on an artificial neural network (ANN) architecture that is able to learn a specific human behavior and can be used in different socio-economic systems. After a training process, the system can identify and classify a human subject using a list of parameters. The model can be further used to analyze and build a safe socio-technical system (STS). A new technique is applied to find an optimal architecture of the neural network. The system shows a good accuracy of the classifications even for a relatively small amount of training data. Starting from a previous result on adaptive forecasting, the model is enhanced by using the retraining technique for an enlarged data set.
artificial neural network, training process, classification, socio-technical system