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

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Pubblicato in:	Journal of Marine Science and Engineering vol. 13, no. 7 (2025), p. 1325-1348
Autore principale:	Bolin, Su
Altri autori:	Wang, Haozhong, Zhu Xingyu, Song Penghua, Li, Xiaolei
Pubblicazione:	MDPI AG
Soggetti:	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
Accesso online:	Citation/Abstract Full Text + Graphics Full Text - PDF
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