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This is a Quantitative Study study (also classified as: Experimental Study).

September 29, 2025The International Journal of Acoustics and VibrationOpen Access

Study on the Sound Absorption Performance of Three Cycle Minimum Surface Based on Convolutional Neural Network

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Authors

BYBinxia YuanShanghai University of Electric Power HJHaopeng JianBeihang University TYTianqi YouNational University of Defense Technology

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Implication

This analysis demonstrates sound absorption capabilities of three cycle minimum surface structures, indicating deep learning's role in performance prediction.

Key Points

The optimized convolutional neural network model achieved an impressive prediction accuracy of 92.52%.
Data enhancement techniques were utilized to expand the dataset for sound absorption performance analysis.
The acoustic performance was simulated using COMSOL software to provide relevant output for the study.
The model's effectiveness was evaluated through various metrics including confusion matrix and ROC curve.

Cite This Study

Yuan et al. (2025) studied this question.

synapsesocial.com/papers/68da58dcc1728099cfd112e0 https://doi.org/10.20855/ijav.2025.30.32143

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Implication

This analysis demonstrates sound absorption capabilities of three cycle minimum surface structures, indicating deep learning's role in performance prediction.

Study on the Sound Absorption Performance of Three Cycle Minimum Surface Based on Convolutional Neural Network

Discussion

Member takes

Implication

Key Points

Cite This Study

Study on the Sound Absorption Performance of Three Cycle Minimum Surface Based on Convolutional Neural Network

Discussion

Member takes

Implication

Key Points

Cite This Study

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