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In their study, a predictive model was designed to predict equipment downtime using machine breakdown periods and maintenance repair time as dependent variable.
Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant.
The Vienna RNA package was probably a comprehensive RNA secondary structure prediction and comparison tool [ 12], and RNALfold was designed to predict locally stable RNA structures in single genome [ 13].
First, the analyses use the logistic EuroSCORE which was designed to predict in-hospital mortality for adjustment, meaning that most important risk factors deemed predictive of short-term outcomes are adjusted for.
The synthesized neural network was designed to predict the parameter value of the model in question.
Based on the model order, an appropriately structured FNS model was designed to predict system faults.
The model was designed to predict both instantaneous and time-averaged pheromone concentrations.
In addition, an artificial neural network (ANN) model was designed to predict the mass transfer performance.
Finally, an optimal artificial neural network was designed to predict the thermal conductivity ratio of the magnetic nanofluid.
The Predictors study was designed to predict the length of time to major disease outcomes in Alzheimer's disease (AD) patients.
The REVEAL score was designed to predict 1-year survival in patients with pulmonary arterial hypertension (PAH) only.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com