期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Machine Learning Application for Prediction of Sapphire Crystals Defects 被引量:1
1
作者 Yulia Vladimirovna Klunnikova Maxim Vladimirovich Anikeev +1 位作者 Alexey Vladimirovich Filimonov Ravi Kumar 《Journal of Electronic Science and Technology》 CAS CSCD 2020年第1期1-9,共9页
We investigate the impact of different numbers of positive and negative examples on machine learning for sapphire crystals defects prediction. We obtain the models of crystal growth parameters influence on the sapphir... We investigate the impact of different numbers of positive and negative examples on machine learning for sapphire crystals defects prediction. We obtain the models of crystal growth parameters influence on the sapphire crystal growth. For example, these models allow predicting the defects that occur due to local overcooling of crucible walls in the thermal node leading to the accelerated crystal growth. We also develop the prediction models for obtaining the crystal weight, blocks, cracks, bubbles formation, and total defect characteristics. The models were trained on all data sets and later tested for generalization on testing sets, which did not overlap the training set.During training and testing, we find the recall and precision of prediction, and analyze the correlation among the features. The results have shown that the precision of the neural network method for predicting defects formed by local overcooling of the crucible reached 0.94. 展开更多
关键词 DEFECTS MACHINE LEARNING SAPPHIRE CRYSTALS
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部