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A deep learning-based approach for predicting oil production: A case study in the United States
2 references·0 citing·12 second hopsampled
A deep learning-based approach for predicting oil production: A case study in the United States (2023)A deep learning-based approach for predic…Deep learning framework for predictive modeling of crude oil price for sustainable management in oil markets (2022)Deep learning framework for p…A novel structure adaptive fractional discrete grey forecasting model and its application in China’s crude oil production prediction (2022)A novel structure adaptive fr…Control problems of grey systems (1982)Discrete grey forecasting model and its optimization (2008)Grey system model with the fractional order accumulation (2012)A novel self-adaptive fractional multivariable grey model and its application in forecasting energy production and conversion of China (2022)Forecasting China's electricity generation using a novel structural adaptive discrete grey Bernoulli model (2023)Natural gas consumption forecasting using an optimized Grey Bernoulli model: The case of the world’s top three natural gas consumers (2023)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Comparing Predictive Accuracy (1995)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A dynamic clustering ensemble learning approach for crude oil price forecasting (2023)Forecasting the lithium mineral resources prices in China: Evidence with Facebook Prophet (Fb-P) and Artificial Neural Networks (ANN) methods (2023)Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models (2023)
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References

  • 2022Deep learning framework for predictive modeling of crude oil price for sustainable management in oil markets56 cited
  • 2022A novel structure adaptive fractional discrete grey forecasting model and its application in China’s crude oil production prediction42 cited

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