ArticleSensors (Basel, Switzerland)2023
The Smart Predicting of Algal Concentration for Safer Drinking Water Production with Sensor Data.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
Abstract
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 in the hidden layer and the permutation and combination of factors, etc., were fully scanned to select the best models and highly correlated factors. All the factors involved in the modeling and selection included the date (year/month/day), sensor data (temperature, pH, conductivity, turbidity, UV254-dissolved organic matter, etc.), lab measurements (algae concentration) and calculated CO
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Registered trials
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