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APPARATUS AND METHOD FOR PROPERTY JOINT INTERPOLATION AND PREDICTION

机译:用于属性关节插值和预测的装置和方法

摘要

According to an aspect of the disclosure there is provided a method for predicting a property associated with a product unit. The method may comprise obtaining a plurality of data sets, wherein each of the plurality of data sets comprises data associated with a spatial distribution of a parameter across the product unit, representing each of the plurality of data sets as a multidimensional object, obtaining a convolutional neural network model trained with previously obtained multidimensional objects and properties of previous product units, and applying the convolutional neural network model to the plurality of multidimensional objects representing the plurality of data sets, to predict the property associated with the product unit.
机译:根据本公开的一方面,提供了一种用于预测与产品单元相关联的特性的方法。该方法可以包括获得多个数据集,其中多个数据集的每个包括与跨产品单元的参数的空间分布相关联的数据,该数据单元将多个数据集的每个表示为多维对象,获得卷积用先前获得的多维对象和先前产品单元的属性训练的神经网络模型,并将卷积神经网络模型应用于代表多个数据集的多个多维对象,以预测与产品单元关联的属性。

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