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