A Deep Learning Approach for Wave Forecasting Based on a Spatially Correlated Wind Feature, with a Case Study in the Java Sea, Indonesia
- DOI
- 10.3390/fluids7010039
- Published
- 2022-01-17
- Container
- Fluids
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/fluids7010039,
title = {A Deep Learning Approach for Wave Forecasting Based on a Spatially Correlated Wind Feature, with a Case Study in the Java Sea, Indonesia},
author = {Didit Adytia and Deni Saepudin and Sri Redjeki Pudjaprasetya and Semeidi Husrin and Ardhasena Sopaheluwakan},
year = {2022},
journal = {Fluids},
doi = {10.3390/fluids7010039},
url = {https://doi.org/10.3390/fluids7010039}
}RIS
TY - JOUR TI - A Deep Learning Approach for Wave Forecasting Based on a Spatially Correlated Wind Feature, with a Case Study in the Java Sea, Indonesia AU - Didit Adytia AU - Deni Saepudin AU - Sri Redjeki Pudjaprasetya AU - Semeidi Husrin AU - Ardhasena Sopaheluwakan PY - 2022 JO - Fluids DO - 10.3390/fluids7010039 UR - https://doi.org/10.3390/fluids7010039 ER -
APA
Adytia, D., Saepudin, D., Pudjaprasetya, S. R., Husrin, S., & Sopaheluwakan, A. (2022). A Deep Learning Approach for Wave Forecasting Based on a Spatially Correlated Wind Feature, with a Case Study in the Java Sea, Indonesia. Fluids. https://doi.org/10.3390/fluids7010039
Source records
- crossref · retrieved 2026-11-10T01:28:48.915Z