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  • 标题:Fuzzy Clustering based Methodology for Multidimensional Data Analysis in Computational Forensic Domain
  • 本地全文:下载
  • 作者:Kilian Stoffel ; Paul Cotofrei ; Dong Han
  • 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
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