Intelligence preparation of the battlefield (IPB) is important in assessing situation and threat missions in military operations. However, existing systems for situation assessment and threat assessment provide insufficient information. In the real world, undiscovered and unidentified threat units, incomplete messages, and enemy deception may cause expert systems to infer unreliable products. Military decision-making systems may suffer from incomplete, inconsistent, and incorrect intelligence. In this paper, we propose a new framework of a knowledge-based system, STAFS, that is more suitable for military applications. STAFS will solve some of these problems using the assumption-based truth maintenance system (ATMS), spatio-temporal reasoning, and uncertainty processing technologies and provide enhanced products to commanders and intelligence staff. STAFS is a near real-time knowledge-based IPB automation system.


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    Titel :

    Situation/Threat Assessment Fusion System (STAFS)


    Beteiligte:
    Jeung Won Choi, (Autor:in) / Jae Woo Joo, (Autor:in) / Dong Lae Cho, (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    656491 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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