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Models for predicting perception of an item of interest
Models for predicting perception of an item of interest
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机译:预测感兴趣项目感知的模型
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摘要
Statistical models for quantifying and predicting human perception of scratches on automotive components are disclosed. Such models may be created by utilizing quantitative two-step moving scale surveys. Such surveys employ a continuous scale to model human perception and allow response bias and measurement error in survey data to be evaluated. Once survey data is collected, relationships between the visual perception of the scratches and the measurable optical properties associated with the scratches can be determined. Additionally, relationships between the visual perception of the scratches and the actual physical scratch dimensions can be determined. Thereafter, models for predicting the human perception of such scratches can be created therefrom. Since these models predict the results of such surveys, the need for repeatedly collecting survey data is eliminated. These models may also be used for predicting human perception of other items of interest. Furthermore, the two-step moving scale surveys may be used in various kinds of surveys about any items of interest.
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