使用视觉分析的自适应态势感知

M. Habibi
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引用次数: 3

摘要

对环境的准确估计是意识到感兴趣的对象周围情况的先决条件。认识必须导致更好、改进和更安全的环境,并在许多情况下避免灾难。根据人类认知本质的线索,态势感知(SAW)模型的发展及其在广泛的工业、医疗和国防应用中的实施取得了重大进展。收集到的信息,如果按照优先级的等级顺序加以利用,就可以在一定程度的信心下做出准确的决策。当前应用中面临的挑战是信息的传播及其演示,当它超出人类思维的感知或理解时,做出人工智能决策。本文详细介绍了自适应态势感知(SAW)的设计方法及其开发所需的组件。阐述了智能可视化分析的特点及其在SAW发展中的重要性。最后,从数据生成、融合、逻辑搜索算法、协议开发等方面入手,利用概率方法的数学建模,提出了一种基于确定性的自适应声SAW模型,并利用可视化分析模型自下而上地实现自适应声SAW的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Situation Awareness Using Visual Analytics
The accurate estimation of environment is a precursor to awareness of the situation around subject(s) of interest. It is imperative that awareness leads to better, improved and safer surroundings and in many cases averts disasters. Following clues from human cognitive nature there have been a significant progress in the development of situation awareness (SAW) models and its implementation in wide ranging industrial, medical and defense applications. The information collected, when utilized in hierarchical order of priority, allows for accurate decision making up to certain degree of confidence. The challenges faced in current applications are the dissemination of information and its demonstration to make artificially intelligent decisions when it goes beyond the perception or comprehension of human mind. In this paper a design methodology is detailed related to adaptive situation awareness (SAW), and the components that are required for its development. The features of intelligent visual analytics and its importance in the development of SAW are also explained. Finally an approach is laid out for arriving at an adaptive SAW with the help of visual analytics model in a bottom up approach, starting from data generation, fusion, logical search algorithm, protocol development and using mathematical modeling for probabilistic approach to a certainty based adaptive SAW model.
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