Machine learning-based semiconductor manufacturing yield prediction system and method
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United States of America Patent
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Nov 8, 2022
Grant Date -
Sep 19, 2019
app pub date -
Nov 29, 2017
filing date -
Nov 30, 2016
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Abstract
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.
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