It is found that, ARMA model is effectively forecasting the ionospheric delay with an accuracy of 82 94%, which is 10% more superior to ARIMA and Holt-Winter's models.
The results clearly indicate that the proposed model effectively improves the forecasting performance and decreases the negative impact of increasing forecast lead time.
In future work, therefore, we expect that expression-based signatures, representing inflammatory cell infiltration and cytokine activity, can be integrated with genetic information to create multivariate models that effectively forecast treatment outcomes on an individual basis.
Simulations of battery and electrolyte temperature at both constant and varying environmental temperatures show that the presenting model is able to effectively forecast the fluctuation of the battery temperature in the presence of different charge and discharge currents.
In this paper, a hybrid wavelet neural network (HWNN) model is developed for effectively forecasting monthly rainfall from antecedent monthly rainfall and climate indices by incorporating the multiresolution analysis (MRA), mutual information (MI) and particle swarm optimization (PSO) into artificial neural network (ANN) models.
The uncertainty analysis of the model results demonstrate that the GRNN can effectively forecast the DO content, since the distribution of model results are very similar to the corresponding distribution of real data.
The dynamic characteristic of the mill can be effectively forecasted using the established model.
Berg et al. (2015) demonstrated this promising method by using a hybrid of the weather research and forecasting (WRF) model with the empirical orthogonal function to effectively forecast precipitation changes.
It is obvious that EMR can be used to effectively forecast the rockburst.
2Local Forecast Model used for forecasts (see Figure 4).
