Sentence examples for be utilized to forecast from inspiring English sources

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It is found that for developing and developed economies, forecasted EEC trends are significantly different, as expected, and IPSO ANN model can be utilized to forecast long-term EEC up to 2030 with mean absolute percentage error of 1.94 and 1.51% for Iran and the U.S., respectively.

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Firstly an ELM is utilized to forecast the short-term wind power.

The wavelet analysis was utilized to capture multiscale data characteristics, while a real neural network (RNN) was utilized to forecast crude oil prices at different scales.

A stacked denoising autoencoder (SDA) model, a class of deep neural networks (DNN), and its extended version are utilized to forecast the daily electricity price profile.

In [19], several methods with some economic data as inputs are utilized to forecast the monthly average price, and the best mean absolute percentage error (MAPE) in these methods is 12.97%.

In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component.

Subsequently, this model is utilized to forecast the real pattern of genes' differential expression.

These models can be utilized to study production forecast and for performing sensitivity studies while retaining the complexity of the heterogeneous reservoir.

It can also be utilized to recognize formation properties and forecast the dynamics of pressure and the production of tight gas reservoirs.

The model presented here can be utilized to recognize formation properties and forecast the pressure and rate dynamics of tight gas reservoirs.

According to Hong and Fan [3], the combination of two or three of the following component can be utilized to generate probabilistic load forecasts: creating input scenario simulation, designing probabilistic models, and transforming point forecasts to probabilistic forecasts through post-processing.

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