文章基本信息

标题：Fuzzy Clustering based Methodology for Multidimensional Data Analysis in Computational Forensic Domain
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作者：Kilian Stoffel ; Paul Cotofrei ; Dong Han 等
期刊名称：International Journal of Computer Information Systems and Industrial Management Applications
印刷版ISSN：2150-7988
电子版ISSN：2150-7988
出版年度：2012
卷号：4
页码：400-410
出版社：Machine Intelligence Research Labs (MIR Labs)
摘要：As interdisciplinary domain requiring advanced and innovative methodologies, the computational forensics domain is characterized by data being, simultaneously, large scaled and uncertain, multidimensional and approximate. Forensic do- main experts, trained to discover hidden pattern from crime data, are limited in their analysis without the assistance of a computational intelligence approach. In this paper, a method- ology and an automatic procedure, based on fuzzy set theory and designed to infer precise and intuitive expert-system-like rules from original forensic data, is described. The main steps of the methodology are detailed, as well as the experiments con- ducted on forensic data sets - both simulated data and real data, representing robberies and residential burglaries.
关键词：fuzzy inference system; fuzzy clustering; forensic;data; computational intelligence