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Forecasting annual natural gas consumption in USA: Application of machine learning techniques- ANN and SVM

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  • Singh, Sanjeet
  • Bansal, Pooja
  • Hosen, Mosharrof
  • Bansal, Sanjeev K.

Abstract

•The current study examines the factors affecting Natural Gas Consumption and their role in the prediction of annual Natural Gas Consumption in the USA.•The study utilizes and compares two machine learning-based forecasting models - support vector machine (SVM) and artificial neural network (ANN) along with traditional multiple linear regression.•The annual data for the period from 1980 to 2020 is collected for the selected influence factors and NGC for prediction.•Based on the MAPE criterion the best model was chosen to be ANN with one nodal value and one hidden layer.•The predicted NGC values indicate a decreasing trend over the period 2021–2030.

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  • Singh, Sanjeet & Bansal, Pooja & Hosen, Mosharrof & Bansal, Sanjeev K., 2023. "Forecasting annual natural gas consumption in USA: Application of machine learning techniques- ANN and SVM," Resources Policy, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s030142072200602x
    DOI: 10.1016/j.resourpol.2022.103159
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    2. Wang, Jia & Wang, Xinyi & Wang, Xu, 2024. "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    3. Li, Xiaobin & Sengupta, Tuhin & Si Mohammed, Kamel & Jamaani, Fouad, 2023. "Forecasting the lithium mineral resources prices in China: Evidence with Facebook Prophet (Fb-P) and Artificial Neural Networks (ANN) methods," Resources Policy, Elsevier, vol. 82(C).
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    5. Xin Zhou & Xin Meng & Zhenyu Li, 2024. "ANN-LSTM-A Water Consumption Prediction Based on Attention Mechanism Enhancement," Energies, MDPI, vol. 17(5), pages 1-16, February.
    6. Yousaf Raza, Muhammad & Lin, Boqiang, 2023. "Development trend of Pakistan's natural gas consumption: A sectorial decomposition analysis," Energy, Elsevier, vol. 278(PA).
    7. Diana M Nova Díaz & Aritz Adin & Eduardo Sánchez Iriso, 2024. "QALYs in adults with cerebral palsy: Mapping from the San Martin Scale onto the EQ-5D-5L instrument," Working Papers 2024-07, FEDEA.
    8. Merve Kayacı Çodur, 2023. "Ensemble Machine Learning Approaches for Prediction of Türkiye’s Energy Demand," Energies, MDPI, vol. 17(1), pages 1-25, December.

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