模糊关系方程在威胁分析中的应用

A. Berrached, M. Beheshti, A. Korvin, R. Aló
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引用次数: 13

摘要

战场上车辆的瞄准行为(目标分析)是计算机生成力量(CGF)系统的关键任务之一。这仅仅是因为在现实世界中有许多复杂和模糊的因素会影响这种系统的目标行为。包括模糊集理论在内的许多方法都被用于目标分析。目标检测和威胁分析与选择是目标分析与选择的主要内容。我们介绍了一个模型来说明如何将模糊关系方程算法应用于计算机生成的力系统(如ModSAF(模块化半自动力))的威胁分析。该算法利用模糊关系方程,从历史信息和早期运行中生成数据。因此,算法的每一个新结果都比之前的结果更真实,更准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying fuzzy relation equations to threat analysis
Targeting behavior of vehicles in the battlefield (target analysis) is one of the most critical tasks in computer generated force (CGF) systems. This is simply because of many complex and ambiguous factors that can affect the targeting behavior of such systems in the real world. There have been many approaches including using fuzzy set theory for target analysis. Target detection, and threat analysis and selection are considered the main constituents of target analysis and selection. We introduce a model to illustrate how to apply a fuzzy relational equation algorithm to threat analysis in the context of computer generated force systems such as ModSAF (Modular Semi Automated Forces). Using fuzzy relational equations, the proposed algorithm generates data from the historic information and its earlier runs. Therefore, each new outcome of the algorithm is more realistic and more accurate than the earlier one.
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