Sentence examples for based on mean absolute from inspiring English sources

The prediction accuracies of the empirical models are evaluated based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Standard Error Deviation SEDD).

The consistent accuracy of the proposed solver is verified through results of statistics in terms of different performance indices based on mean absolute error, root mean square error and Nash-Sutcliffe efficiency.

The performance of the proposed scheme is validated through the comparison of results from Adam numerical method with the help of different measures based on mean absolute derivation, root mean square error, and Nash-Sutcliffe efficiency.

In order to predict censored survival time, martingale residuals were calculated as a new continuous outcome and a new fitness function used by the grammatical evolution neural network (GENN) based on mean absolute difference of martingale residuals was implemented.

A large number of simulations are performed for the proposed scheme to determine its effectiveness and reliability through different performance indices based on mean absolute deviation, Nash-Sutcliffe efficiency, and Thiel's inequality coefficient.

The accuracy and convergence of the proposed solver are validated through sufficient large numbers of independent runs in terms of different performance indices based on mean absolute error, Thail's inequality coefficient and Nash-Suitcliff efficiency.

Most of the improvements were at the slight to moderate levels, e.g., 3.66 14.24% increases in the accuracy based on mean error, mean absolute error, root mean square error and R2.

Results of statistical analysis in terms of performance measures based on mean, standard deviation, mean absolute deviation, root mean square error and Nash Sutcliffe efficiency as well as their global variations further established the worth of the given scheme for each variant of drainage problem.

Based on mean sum squared error (MSE) and absolute average error in prediction (AEp) of training and testing data, an optimum feed forward neural network based on back propagation was developed with 3 input neurons, 2 hidden layers, 6 neurons in each hidden layer and 1 output neuron 3-6-6-1 3-6-6-1 3-6-6-1 3-6-6-1

Finally, a GMS filter-based architecture based on the mean absolute errors criterion is adopted to build a non-linear multi-class classifier.

The best ANN algorithm and model are identified based on minimum mean absolute error (MAE) and root mean square error (RMSE) and maximum linear correlation coefficient (R).