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The model efficiency is demonstrated on well-known problems such as the 2-spirals or waveforms.
Organizational operations courses model efficiency with proven mathematical formulas to improve it.
Methods of dramatically improving joint model efficiency were highlighted.
The match is primarily evaluated using the Nash-Sutcliffe (NS) model efficiency.
Among all models, the two-site + AWI model achieved consistently high model efficiency for all experiments.
Multi-criteria evaluation of ANN models is recommended for better interpretation of model efficiency.
A gap-search algorithm was designed to enhance the model efficiency.
The validation results confirm the model efficiency in providing long-term decisions in a dynamic environment.
The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS).
The ANFIS method resulted in higher model efficiency and coefficient of determination (R2 = 0.91) than MLR approach (R2 = 0.74).
Water flow simulations produced model efficiency of 0.84 for control (CONT) and 0.56 for MULCH systems, while nitrate simulations showed model efficiency ranging from 0.67 to 0.83 and from 0.70 to 0.93, respectively.
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