The Smart Predicting of Algal Concentration for Safer Drinking Water Production with Sensor Data

To better predict the timely variation of algal blooms and other vital factors for safer drinking water production, a new AI scanning–focusing process was investigated for improving the simulation and prediction of algae counts. With a feedforward neural network (FNN) as a base, nerve cell numbers i...

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Detalles Bibliográficos
Autores principales: Yu, Han, Li, Jing, Holmer, Linda, Köhler, Stephan J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255630/
https://www.ncbi.nlm.nih.gov/pubmed/37299878
http://dx.doi.org/10.3390/s23115151

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255630/
https://www.ncbi.nlm.nih.gov/pubmed/37299878
http://dx.doi.org/10.3390/s23115151

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