Accurate Prediction and Reliable Parameter Optimization of Neural Network for Semiconductor Process Monitoring and Technology Development

Accurate Prediction and Reliable Parameter Optimization of Neural Network for Semiconductor Process Monitoring and Technology Development

Herein, novel neural network (NN) methods that improve prediction accuracy and reduce output variance of the optimized input in the gradient method for cross‐sectional data are proposed, and the variability evaluation approach of optimized inputs in the semiconductor process is suggested. Specifical...

Podrobná bibliografie
Hlavní autoři:	Hyeok Yun, Chang-Hyeon An, Hyundong Jang, Kyeongrae Cho, Jeong-Sik Lee, Seungjoon Eom, Choong-Ki Kim, Min-Soo Yoo, Hyun-Chul Choi, Rock-Hyun Baek
Médium:	Článek
Jazyk:	English
Vydáno:	Wiley 2023-09-01
Edice:	Advanced Intelligent Systems
Témata:	gradient descent method holistic parameter optimization machine learning network ensemble neural networks semiconductor manufacturing
On-line přístup:	https://doi.org/10.1002/aisy.202300089

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