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A Water Quality Prediction Method Based on the Deep LSTM Network Considering Correlation in Smart Mariculture
An accurate prediction of cage-cultured water quality is a hot topic in smart mariculture. Since the mariculturing environment is always open to its surroundings, the changes in water quality parameters are normally nonlinear, dynamic, changeable, and complex. However, traditional forecasting method...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470961/ https://www.ncbi.nlm.nih.gov/pubmed/30909468 http://dx.doi.org/10.3390/s19061420 |