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MACHINE LEARNING-BASED SEMICONDUCTOR MANUFACTURING YIELD PREDICTION SYSTEM AND METHOD

机译:基于机器学习的半导体制造产量预测系统和方法

摘要

Provided is a machine learning-based semiconductor manufacturing yield prediction system and method. A result prediction method according to an embodiment of the present invention comprises: learning different neural network models by classifying different types of data according to their types and respectively inputting the classified different types of data to the different neural network models; and predicting result values by classifying input data according to their types and respectively inputting the classified input data to different neural network models. Therefore, it is possible to apply different neural network models to respective data according to their types, thereby ensuring a neural network model having a structure appropriate for the characteristics of each type of data and thus accurately predicting a result value.
机译:提供了一种基于机器学习的半导体制造良率预测系统和方法。根据本发明实施例的结果预测方法包括:通过根据数据的类型对不同类型的数据进行分类来学习不同的神经网络模型,并将分类后的不同类型的数据分别输入至不同的神经网络模型;通过根据输入数据的类型对输入数据进行分类并将分类后的输入数据分别输入到不同的神经网络模型,从而预测结果值。因此,可以根据它们的类型将不同的神经网络模型应用于各自的数据,从而确保神经网络模型具有适合于每种数据类型的特性的结构,从而准确地预测结果值。

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