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At the end of the incubation, the effects of amendments on the assessed variables as well as the process modelling were evaluated by Response Surface Methodology (RS M.
Two different approaches for the selection of a limited set of compounds for modelling were evaluated through the predictive power of the resulting QSAfR models.
In this study, the performances of polynomials, radial basis functions (RBFs) and multilayer perceptron (MLP) neural network algorithms used in local geoid surface modelling were evaluated in the study area.
Similar(57)
Two and three compartment models were evaluated.
Six different models were evaluated.
Three explanatory models were evaluated.
Best-fit models were evaluated using jModeltest.
The models were evaluated using LOCOCV.
The models were evaluated using MPE, NSE, RMSE and MBE.
Infiltration models were evaluated using C.C, NSE and RMSE methods.
These models were evaluated using synthetic and real data sets.
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