Cargando…
Aquaculture 4.0: hybrid neural network multivariate water quality parameters forecasting model
This study examined the efficiency of hybrid deep neural network and multivariate water quality forecasting model in aquaculture ecosystem. Accurate forecasting of critical water quality parameters can allow for timely identification of possible problem areas and enable decision-makers to take pre-e...
Autores principales: | Eze, Elias, Kirby, Sam, Attridge, John, Ajmal, Tahmina |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522619/ https://www.ncbi.nlm.nih.gov/pubmed/37752237 http://dx.doi.org/10.1038/s41598-023-41602-7 |
Ejemplares similares
-
The Evolution Road of Seaweed Aquaculture: Cultivation Technologies and the Industry 4.0
por: García-Poza, Sara, et al.
Publicado: (2020) -
Forecasting water quality parameters using artificial neural network for irrigation purposes
por: Ubah, J. I., et al.
Publicado: (2021) -
Transformers for Multi-Horizon Forecasting in an Industry 4.0 Use Case
por: Vakaruk, Stanislav, et al.
Publicado: (2023) -
Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters
por: Zare Abyaneh, Hamid
Publicado: (2014) -
Recurrent neural network modeling of multivariate time series and its application in temperature forecasting
por: Nketiah, Edward Appau, et al.
Publicado: (2023)