生产动态的数据驱动建模

2022 International Symposium on Semiconductor Manufacturing (ISSM) Pub Date : 2022-12-12 DOI:10.1109/ISSM55802.2022.10026908

S. Arima, Yu Sasaki, Sho Morie, Yuto Kataoka, Chending Mao, Jia Lin

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引用次数: 0

摘要

本文介绍了应用VAR-LiNGAM和基于node2vec的反向传播神经网络，对规模和复杂性日益增加的半导体生产系统进行可行的数据驱动动力学建模。开放试验台SMT2020是用来评估的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Data-driven Modeling for Production Dynamics

This study introduced the application of VAR-LiNGAM, and Backpropagation Neural Network with node2vec for feasible data-driven modeling of dynamics of semiconductor production system in which the scale and complexity increase more and more. Open testbed SMT2020 is used evaluations.

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来源期刊

2022 International Symposium on Semiconductor Manufacturing (ISSM)

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