A Neuro-Classification Model for Socio-Technical Systems
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.
Volume (Year): 6 (2009)
Issue (Month): 3 (September)
|Contact details of provider:|| Postal: Casa Academiei, Calea 13, Septembrie nr.13, sector 5, Bucureşti 761172|
Phone: 004 021 3188148
Fax: 004 021 3188148
Web page: http://www.ipe.ro/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:rjr:romjef:v:6:y:2009:i:3:p:100-109. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman)
If references are entirely missing, you can add them using this form.