Efficient Prediction of Shallow-Water Acoustic Transmission Loss Using a Hybrid Variational Autoencoder–Flow Framework

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Bibliografiska uppgifter
I publikationen:	Journal of Marine Science and Engineering vol. 13, no. 7 (2025), p. 1325-1348
Huvudupphov:	Bolin, Su
Övriga upphov:	Wang, Haozhong, Zhu Xingyu, Song Penghua, Li, Xiaolei
Utgiven:	MDPI AG
Ämnen:	Accuracy Shallow water Datasets Flow Transmission loss Mapping Computer applications Batch processing Telecommunications Deep learning Prediction models Propagation Computation Acoustics Sound transmission Neural networks Computational efficiency Sound velocity Variables Communications systems Controllability Physical properties Learning Underwater Computing time Waveguides Environmental
Länkar:	Citation/Abstract Full Text + Graphics Full Text - PDF
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