Sentence examples for mean bias error from inspiring English sources
The model efficiency is high, and the mean bias error and root mean bias error between the simulated and the observed values are minor.
Mean absolute error and mean bias error were adopted for accuracy assessment of the models.
These differences were also compared with the mean bias error and root-mean-squared error of the modelled GSR.
The most appropriate interpolation method was selected based on mean absolute error (MAE) and mean bias error (MBE) indices.
For each state, a series of 1000 retrieval simulations are performed to evaluate the mean bias error and the RMSE.
The mean absolute errors (MAEs) and mean bias errors (MBEs) in the downscaled maximum daily temperature based on 30 weather stations reveal that the elevation-based downscaling approach is effective and the average errors do not significantly affect the spatial and temporal patterns of heating cycles in terms of the four key variables and frequency distributions of heating cycles.
Overall mean bias errors (MBE) below 9% and root mean square errors (RMSE) below 19% demonstrate that translucent materials can be modeled in Radiance with an even higher accuracy than was demonstrated in earlier validation studies for the plastic, metal, and glass material types.
Having Root Mean Square Errors (RMSE) in the range of 0.54 2.07 mm, HYDRUS-2D ranked first for the SWC estimation, while the ANFIS and SVM models with input datasets of cGDD, Kc, WD and In ranked next with RMSEs ranging from 1.27 to 1.9 mm and mean bias errors of −0.07 to 0.27 mm, respectively.
The model presented has a considerably higher correlation coefficient (0.963) and lower root mean square (0.375), mean absolute (0.328), and mean bias errors (0.010) than other models presented in the literature which, at least when applied to the present data set, tend to under-predict the combustion enthalpy.
In order to evaluate the day by day performance of these models, a statistical analysis was performed by using several statistical indicators of mean absolute bias error, root mean square error, normal root mean square error, test statistic, standard deviation and coefficient of determination.
