JIST

Journal of Information Science and Technology

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Vol 2 Iss 3 Article 3

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icon Eyewitness Information Management System Using Neuro-fuzzy Classification Schemes (169.59 kB)

 

Title: Eyewitness Information Management System Using Neuro-fuzzy Classification Schemes

 

Author(s): Adedeji B. Badiru, O. Sunday Asaolu, & Olufemi A. Omitaomu

 

Abstract:

The use of computers in law enforcement has been generally recognized and widely reported in the literature and recent popular press. Law enforcement generates and deals with greater volume of data that takes a lot of time to collate and work with. Previous successes with the use of software tools in law enforcement have paved the way for new and innovative applications of software techniques to aid crime data management and investigation. The emerging area of homeland security is a particularly fertile area of application for software-based investigative tools. Recent developments in fuzzy systems and artificial neural networks have led to the emergence of hybrid software systems that are effective for a variety of ill-structured problems such as crime investigation. One solution to such problems is based on a combination of expert rules, fuzzy logic reasoning, prediction capabilities of artificial neural networks, and the data handling power of computers. This paper presents the development of robust software capable of utilizing and cross-referencing generic problems of witness accounts, crime scene data, and investigators’ experiential reasoning. The software, named EyeWitness Account (EWA), uses neuro-fuzzy classification schemes for suspect identification based on eyewitness accounts.

Last Updated on Thursday, 30 June 2011 15:36