Auto-Identification of a Drug Seller Utilizing a Specialized Supervised Neural Network

Chapter

Abstract

This chapter addresses the problem of pattern recognition in drug enforcement: how an ensemble of artificial adaptive systems is able to distinguish between different ranks of drug dealers using only the limited features available from felons at the moment of arrest. A subset of the most promising features are selected from the set of all possible features utilizing the “TWIST” system; a collection of classical back-propagation artificial networks are used for pattern recognition tasks, and a new metaclassifier algorithm is shown to optimize the final intelligent classification.

References

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Software

  1. Buscema, M. (1999–2011). Supervised ANNs and Organisms, Semeion Software #12, ver. 18.0, Rome (Italy).Google Scholar
  2. Buscema, M. (2006–2007). Twist – Input Search and Training & Testing Reverse, Semeion Software #39, ver. 2.0, Rome (Italy).Google Scholar
  3. Buscema, M. (2008–2). Meta Net, Semeion Software #44, ver. 8.0, Rome (Italy).Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Semeion Research Center of Sciences of CommuicationRomeItaly

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