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

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Detalles Bibliográficos
Publicado en:	Journal of Marine Science and Engineering vol. 13, no. 7 (2025), p. 1325-1348
Autor principal:	Bolin, Su
Otros Autores:	Wang, Haozhong, Zhu Xingyu, Song Penghua, Li, Xiaolei
Publicado:	MDPI AG
Materias:	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
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
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