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- W4312933672 abstract "The production process of Czochralski monocrystalline silicon is a complex process with nonlinear, multi-coupling, and uncertainties, and the equal diameter stage is the most important part of the whole crystal pulling process. However, the current mechanism-based modeling methods have great limitations and one-sidedness, and it is difficult to substantially help the actual production process. In this paper, through a large amount of data collected in the Czochralski silicon single crystal production workshop, and modeling through the fuzzy neural network, the diameter prediction model of the data-driven equal-diameter stage is obtained. The relative error of the test results is only 0.0287%. Experiments were carried out on the other 4 sets of data collected from different single crystal furnaces in the production workshop. The results show that the prediction accuracy of the model can generally reach more than 99.5%, which proves the high accuracy of the prediction model for diameter prediction. At the same time, it lays a good foundation for the model predictive control based on the data-driven equal-diameter stage and can provide theoretical guidance for the control strategy optimization of the actual production in the later stage." @default.
- W4312933672 created "2023-01-05" @default.
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- W4312933672 date "2022-07-28" @default.
- W4312933672 modified "2023-10-18" @default.
- W4312933672 title "Diameter Prediction of Czochralski Silicon Single Crystal with Equal Diameter Based on Fuzzy Neural Network" @default.
- W4312933672 doi "https://doi.org/10.1109/icpet55165.2022.9918515" @default.
- W4312933672 hasPublicationYear "2022" @default.
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