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Canonical Correlation Analysis: Use of Composite Heliographs for Representing Multiple Patterns

机译:规范相关性分析:使用复合光学表格代表多种图案

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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:在与波音757/767飞机的自动飞行控制系统的互动研究方案中,我们观察了60个航班并记录了飞机控制模式的每一个变化,以及操作环境中的每一个可观察变化。为了量化操作环境和飞行员的行动和响应之间的关系,我们使用规范相关性,因为它可以在大型数据集中找到多种模式的独特适用性。传统上,通过数值表介绍了规范相关分析的结果,这不利于识别数据中的多维模式。我们创建了一种像亚历山大的中心理论,呈现出一种太阳光线图(我们称之为高音凹视)以呈现数据中存在的多种模式。该理论描述了15个启发式属性,有助于在设计中创建全能,并且可以扩展到信息抽象和集成的问题以及大量数据的包装以进行可视化。

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