首页> 外文会议>International Conference on Diagrammatic Representation and Inference(Diagrams 2006); 20060628-30; Stanford,CA(US) >Canonical Correlation Analysis: Use of Composite Heliographs for Representing Multiple Patterns
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Canonical Correlation Analysis: Use of Composite Heliographs for Representing Multiple Patterns

机译:典型的相关分析:使用复合Heliographs表示多个模式

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In a study of crew interaction with the automatic flight control system of the Boeing 757/767 aircraft, we observed 60 flights and recorded every change in the aircraft control modes, as well as every observable change in the operational environment. To quantify the relationships between the state of the operating environment and pilots' actions and responses, we used canonical correlation because of its unique suitability for finding multiple patterns in large datasets. Traditionally, the results of canonical correlation analysis are presented by means of numerical tables, which are not conducive to recognizing multidimensional patterns in the data. We created a sun-ray-like diagram (which we call a heliograph) to present the multiple patterns that exist in the data by employing Alexander's theory of centers. The theory describes 15 heuristic properties that help create wholeness in a design, and can be extended to the problem of information abstraction and integration as well as packing of large amounts of data for visualization.
机译:在对机组人员与波音757/767飞机的自动飞行控制系统的互动进行的研究中,我们观察了60次飞行,并记录了飞机控制模式的每一次变化以及运行环境中的每一次可观察到的变化。为了量化操作环境状态与飞行员的行动和响应之间的关系,我们使用规范相关性,因为它具有在大型数据集中查找多个模式的独特适应性。传统上,规范相关分析的结果是通过数值表来表示的,这不利于识别数据中的多维模式。我们采用亚历山大的中心理论,创建了一个类似于太阳光的图表(我们称之为日光照射器)来显示数据中存在的多种模式。该理论描述了15种启发式属性,这些属性有助于在设计中创造整体性,并且可以扩展到信息抽象和集成以及打包大量数据以进行可视化的问题。

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