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A Soft Computing Model to Counter Terrorism


Karthikeyan Marappan, Krishnan Nallaperumal, K. Senthamarai Kannan, B.Bensujin


Vol. 8  No. 5  pp. 141-147


In the aftermath of September 11, the experts concluded that data mining could help it prevent future terrorist attacks. Experts are also concerned that in its zeal to apply technology to antiterrorism, the government could disrupt the crime-fighting processes of the agencies that are charged with finding and stopping terrorists before they act. The entire information or the evidence about a terrorist and the inclined behavior of some personalities are stored in interactive XML sheets (iXML), which are called as trifles, the piece of information. These trifles play a vital role in training the soft computing model and for pattern detection. These trifles in the form of iXML sheets are given in the network for pattern detection. The soft computing model used here is the Competitive Neural Tree (CNeT). The CNeT is the type of decision tree in which each node is compared and a decision will be taken to move to the next. In each stage the pattern recognition is done with the contents of the iXML nodes.


CNet, decision tree, iXML, soft computing, trifle