Soft computing techniques for analysis of kidnapping crimes in Colombia

Abstract

Techniques associated with soft computing have been proven to be useful for solving problems where lack of information and uncertainties are present. The flaws of traditional methodologies stem from the fuzziness, partial true, lack of information, and event imprecision of problems related to crime analysis such as kidnapping. Case based reasoning and expert's knowledge are the main inputs of some soft computing techniques that may be applied for analysis of kidnapping crimes. Kidnapping is a problem framed by the lack of veracity, scarceness, fuzziness of information, and tacit, qualitative and unstructured knowledge in the minds of few experts. So, kidnapping is the kind of problem that could be modeled and analyzed by using some of the techniques included in the field of soft computing. This paper describes the use of fuzzy logic, fuzzy clustering and classification to analyze and evaluate kidnapping crimes in Colombia. These techniques are intended to predict the captivity duration, captor group and liberation conditions for any victim. Also, these techniques could be used to assess the impact of government security and economic policies on the evolution of the kidnapping crime