Chinese Journal of Lasers, Volume. 48, Issue 9, 0901004(2021)
Recognition of Energy Model of Excimer Laser by Gate Recurrent Unit
[6] Zhou C Q, Yu L, Lu P H et al. Effect of asphericity parameter on Seidal aberration and ablation depth in laser refractive surgery[J]. Optics and Precision Engineering, 15, 167-172(2007).
[7] Bi D D, Zhang L C, Shi G et al. Optical coatings for projection objective immersion lithography[J]. Chinese Optics, 11, 745-764(2018).
[8] Petrova T B, Petrov G M, Wolford M F et al. Modeling of an electron-beam pumped Arf excimer laser[C]. //2017 IEEE International Conference on Plasma Science (ICOPS), May 21-25, 2017, Atlantic City, NJ, USA., 1(2017).
[15] Fan Y P, Huang X Y, Yu Y S et al. Adjusting-controlling on gassing and energy for high power excimer laser based on intelligence[J]. Control Theory & Applications, 19, 561-566(2002).
[16] Wang X S, Liang X, You L B et al. Study on energy control algorithm for high-repetition-rate ArF excimer lasers[J]. Laser Technology, 36, 763-766(2012).
[18] Sun Z J, Xue L, Xu Y M et al. Overview of deep learning[J]. Application Research of Computers, 29, 2806-2810(2012).
[20] Chmielewski A, Moẑaryn J, Piórkowski P et al. Battery voltage estimation using NARX recurrent neural network model[M]. //Szewczyk R, Zieliński C, Kaliczyńska M, et al. Automation 2019. Advances in intelligent systems and computing, 920, 218-231(2020).
[21] Abbasi T, Lim K H, Yam K S et al. Predictive maintenance of oil and gas equipment using recurrent neural network[J]. IOP Conference Series: Materials Science and Engineering, 495, 012067(2019).
[24] Agarap A F M. A neural network architecture combining gated recurrent unit (GRU) and support vector machine (SVM) for intrusion detection in network traffic data[C]. //Proceedings of the 2018 10th International Conference on Machine Learning and Computing, February 26, 2018, Macao, China, 26-30(2018).
[26] Amihai I, Chioua M, Gitzel R et al. Modeling machine health using gated recurrent units with entity embeddings and K-means clustering[C]. //2018 IEEE 16th International Conference on Industrial Informatics (INDIN), July 18-20, 2018, Porto., 212-217(2018).
[30] Hochreiter S, Schmidhuber J. LSTM can solve hard long time lag problems[C]. //NIPS’96: Proceedings of the 9th International Conference on Neural Information Processing Systems, December 3, 1996, Cambridge, MA, United States, 473-479(1997).
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Zebin Feng, Yi Zhou, Rui Jiang, XiaoQuan Han, Xiangyu Xu, Bin Liu. Recognition of Energy Model of Excimer Laser by Gate Recurrent Unit[J]. Chinese Journal of Lasers, 2021, 48(9): 0901004
Category: laser devices and laser physics
Received: Sep. 14, 2020
Accepted: Nov. 23, 2020
Published Online: May. 17, 2021
The Author Email: Zhou Yi (zhouyi1@ime.ac.cn), Jiang Rui (jiangrui@ime.ac.cn), Han XiaoQuan (hanxiaoquan@ime.ac.cn)