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NEURAL NET AND DISCRETE EVENT SIMULATIONS OF C2 PERFORMANCE IN ARMY TOCS

机译:军事TOCS中C2性能的神经网络和离散事件模拟

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This project examines command and control (C2) from a system level viewpoint to study the way Tactical Operations Centers (TOC’s) operate and then translates those observations into validated computer simulations using a methodological framework. This approach provides the ability to model TOC operations in a way that not only includes the individuals, work groups and teams in it, but also all of the other hardware and software systems and subsystems and human-system interfaces that comprise it as well as the facilities and environmental conditions that surround it. Datamining procedures, including neural network simulation, are used to screen raw data from naturalistic observation of TOC operations to identify significant relationships for follow-on analysis. Discrete event simulations then utilize mathematical relationships from the neural network analysis to describe TOC operations in a way that can be used for evaluations of new and proposed TOC Systems. The intent of this project is to develop a framework of techniques and procedures that are based upon empirical methods but are usable in real world, uncontrolled environments which can only be approached with naturalistic observation methods.
机译:该项目从系统级的角度检查命令和控制(C2),以研究战术作战中心(TOC)的运行方式,然后将这些观察结果转换为使用方法框架的经过验证的计算机模拟。这种方法提供了对TOC操作进行建模的能力,该方法不仅包括其中的个人,工作组和团队,而且还包括构成该TOC操作的所有其他硬件和软件系统,子系统和人机界面以及周围的设施和环境条件。包括神经网络模拟在内的数据挖掘程序用于从TOC操作的自然观察中筛选出原始数据,以识别重要的关系以进行后续分析。离散事件模拟然后利用神经网络分析中的数学关系来描述TOC操作,该方法可用于评估新的和建议的TOC系统。该项目的目的是开发一种基于经验方法的技术和程序框架,但可在现实世界中不受控制的环境中使用,这些环境只能通过自然观察方法来实现。

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  • 会议地点 New Orleans, LA(US);New Orleans, LA(US)
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    Sam E. Middlebrooks;

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    U.S. Army Research Laboratory Human Research and Engineering Directorate ATTN: AMSRD-ARL-HR-MV Hq. USAOTC 91012 Station Ave.Fort Hood Texas 76544-5073(254) 288-9379 sam.middlebrooks@otc.army.mil;

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