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Verification and validation issues in a generic model of electro-optic sensor systems

机译:电光传感器系统通用模型中的验证和验证问题

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摘要

In general, questions of model credibility introduce more problems in a generic model than they do in models developed for one specific application since a generic\udformulation must allow for many applications of the model. This paper addresses the issues of model testing, verification and validation for a generic electro-optic sensor system model. A structural approach to testing, verification and validation is proposed that builds increasing confidence through bottom-up testing, structured verification procedures and carefully selected validation metrics. These metrics are based on a geometrical view of model outputs that may be compared with measurements using\udqualitative methods or quantitative approaches involving image processing, artificial neural networks or fuzzy pattern recognition. The advantage over traditional\udvalidation methods is most marked in the case of complex models with many key quantities where it not only provides insight about the validity but also about sensitivities. These validation tools have been applied, in conjunction with more traditional metrics, to the testing, verification and validation of the generic model configured as a thermal imager system.
机译:一般而言,模型的可信度问题在通用模型中比在为一个特定应用程序开发的模型中引入更多的问题,因为通用\公式化必须允许模型的许多应用程序。本文讨论了通用光电传感器系统模型的模型测试,验证和确认问题。提出了一种结构化的测试,验证和确认方法,该方法通过自下而上的测试,结构化的验证程序和精心选择的验证指标来增强信心。这些度量基于模型输出的几何视图,可以将其与使用定性方法或涉及图像处理,人工神经网络或模糊模式识别的定量方法的测量结果进行比较。在具有许多关键数量的复杂模型的情况下,与传统的\ udvalidation方法相比,优势最为明显,它不仅可以提供关于有效性的信息,而且还可以提供有关敏感性的信息。这些验证工具已与更传统的度量标准结合在一起,用于配置为热像仪系统的通用模型的测试,验证和确认。

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