• DocumentCode
    1122709
  • Title

    A knowledge-based fatal incident decision model

  • Author

    Manivannan, S. ; Guthrie, S.

  • Author_Institution
    Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    6
  • Issue
    4
  • fYear
    1994
  • fDate
    8/1/1994 12:00:00 AM
  • Firstpage
    534
  • Lastpage
    548
  • Abstract
    A methodology for determining remains identification (ID) following a mass disaster is presented. The solution methodology is domain-independent and capable of addressing a wide range of assignment problems. A knowledge-based fatal incident decision model (FINDM) for providing a decision support to forensic scientists involved in the skeletal ID process is discussed. A mathematical framework for FINDM is developed that integrates a knowledge base with a network flow algorithm for resolving conflicts during the ID process. The FINDM framework has been implemented can an IBM PC and includes an observation advisor, an assignment advisor, and a conflict resolution module. Knowledge acquisition and representation issues are discussed, along with a numerical example and results. With respect to the remains ID problem, the FINDM approach shifts major efforts in resolving the problem from that of establishing a method of assignment to that of controlling the quality of data collected, improving domain knowledge, and analyzing conflicts
  • Keywords
    anthropology; decision support systems; disasters; emergency services; expert systems; knowledge acquisition; knowledge representation; pattern recognition; FINDM; IBM PC; antemortem data; assignment advisor; conflict resolution; contradiction factor; decision support; domain knowledge,; forensic anthropology; forensic scientists; knowledge acquisition; knowledge base; knowledge representation; knowledge-based fatal incident decision model; mass disaster; network flow algorithm; observation advisor; postmortem analysis; regression equations; remains identification; skeletal ID process; trait evaluations; Computer crashes; Data analysis; Earthquakes; Equations; Forensics; Humans; Knowledge acquisition; Large-scale systems; Systems engineering and theory; US Government;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.298171
  • Filename
    298171