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Scrap steel price forecasting with neural networks for east, north, south, central, northeast, and southwest China and at the national level
16 references·8 citing·38 second hop
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References

  • 1988Testing for a Unit Root in Time Series Regression19,288 cited
  • 1981Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root14,647 cited
  • 1992Testing the null hypothesis of stationarity against the alternative of a unit root12,634 cited
  • 1996A test for independence based on the correlation dimension3,526 cited
  • 1997Testing the equality of prediction mean squared errors2,103 cited
  • 2009The Impact of Food Prices on Consumption: A Systematic Review of Research on the Price Elasticity of Demand for Food1,141 cited
  • 2019Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series526 cited
  • 2020A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series481 cited
  • 2020Corn Cash Price Forecasting443 cited
  • 2021Forecasting gold price with the XGBoost algorithm and SHAP interaction values334 cited
  • 2021A hybrid model for carbon price forecastingusing GARCH and long short-term memory network316 cited
  • 1996A comparison of artificial neural network and time series models for forecasting commodity prices293 cited
  • 2021Corn cash price forecasting with neural networks291 cited
  • 2019Indian stock market prediction using artificial neural networks on tick data

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271 cited
  • 2019Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network254 cited
  • 2021Individual time series and composite forecasting of the Chinese stock index241 cited
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    • 2025Machine learning platinum price predictions45 cited
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    • 2025Machine learning predictions of China commodity price indices41 cited