Uncertainty Quantification of Vibroacoustics with Deep Neural Networks and Catmull–Clark Subdivision Surfaces
This study proposes an uncertainty quantification method based on deep neural networks and Catmull–Clark subdivision surfaces for vibroacoustic problems. The deep neural networks are utilized as a surrogate model to efficiently generate samples for stochastic analysis. The training data are obtained...
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| Main Authors: | Zhongbin Zhou, Yunfei Gao, Yu Cheng, Yujing Ma, Xin Wen, Pengfei Sun, Peng Yu, Zhongming Hu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2024/7926619 |
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