The GDP forecast model of Heilongjiang Province was established based on the above improved algorithm and it was compared and analyzed with the traditional ...
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Nov 12, 2021 · Based on the BP neural network and the ARIMA model, this paper predicts the nonlinear residual of GDP and adds the predicted values of the ...
We propose an ensemble learning methodology to forecast the future US GDP growth release. Our approach combines a Recurrent Neural Network (RNN) and a ...
For forecasting purposes with neural networks, we proceed in two different ways. In the first instance, static forecasts are computed, based on the estimation ...
Forecasting the Gross Domestic Product (GDP) of the United States is one of many esti mates to predict the economic health of the countr)>.
We propose an ensemble learning methodology to forecast the future US GDP growth release. Our approach combines a Recurrent Neural Network (RNN) and a ...
Jan 29, 2024 · This paper proposes a new model called Pearson Correlation-Long Short-Term Memory-Recurrent Neural Network (PC-LSTM-RNN) for predicting GDP in ...
May 17, 2022 · The experimental results demonstrate that neural networks were reliable in predicting GDP and can be used for further applications in practice.
An effective combination method according to the GDP characteristics and builds an improved algorithm BP neural network price prediction model is proposed, ...
We propose an ensemble learning methodology to forecast the future US GDP growth release. Our approach combines a Recurrent Neural Network.