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Pictorial analysis: a multi-resolution data visualization approach for monitoring and diagnosis of complex systems

机译:图形分析:用于监视和诊断复杂系统的多分辨率数据可视化方法

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This paper aims to describe the prospective methodology (Pictorial Analysis) of a human-computer interaction capable to select and adjust visual representations for better feature and pattern selection. As an adequate tool for on-line monitoring and diagnosis of very complex systems which require human supervision in addition to the computerized one, our approach exploits human capabilities of pattern recognition in doing data analysis and selecting appropriate representations, features and class descriptions by means of interactive human-computer learning. It is based on the analysis of multidimensional relations through transforming the initial data (heterogeneous arrays, signals and fields) into artificial pictures. Practical applications of this approach prove it extremely useful in critical areas of safety, such as flight control, power plant monitoring, etc. (C) 2003 Published by Elsevier Science Inc. [References: 20]
机译:本文旨在描述人机交互的前瞻性方法(绘画分析),该方法能够选择和调整视觉表示,以实现更好的特征和模式选择。作为对非常复杂的系统进行在线监视和诊断的适当工具,除了需要计算机化的系统外,还需要人工监督,我们的方法利用模式识别的人工能力来进行数据分析并通过以下方式选择合适的表示形式,特征和类别描述:交互式人机学习。它基于对多维关系的分析,方法是将初始数据(异构数组,信号和场)转换为人造图像。这种方法的实际应用证明,它在关键的安全领域(如飞行控制,电厂监控等)极为有用。(C)2003年由Elsevier Science Inc.出版[参考文献:20]

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