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The estimation model estimates the IMEP of each cylinder.
The proposed thermal model estimates the outlet air temperature of the nodes to predict cooling costs.
The model estimates the critical wellbore pressure below which sand production is expected.
The ANN model estimates the surface roughness with high accuracy compared to the multiple regression model.
The model estimates the mass eruption rate from the column height and atmospheric conditions above the vent based on the parameterization of Bonadonna and Costa36.
The stochastic model estimates the probability distributions of potential results by allowing for random variation in inputs over time until the standard deviation of the result is <5%.
Briefly, the model estimates the proportion of terrestrial, benthic and littoral primary production used by fish from stable isotope data and published physiological parameters (see Supplementary Methods).
Our model estimates the energy consumption of a virtual machine based on in-processor events generated by the virtual machine.
The distributed model estimates the pressure losses and time delay through long connected pipelines in real time.
A preliminary model estimates the aeration flowrate which will keep the solids fluidized without large wall jets.
The model estimates the maximum bandgap shift and the effect of process parameters such as exposure time and irradiation energy.
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CEO of Professional Science Editing for Scientists @ prosciediting.com