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A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India

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  1. Gabriela Mayumi Saiki & André Luiz Marques Serrano & Gabriel Arquelau Pimenta Rodrigues & Guilherme Dantas Bispo & Vinícius Pereira Gonçalves & Clóvis Neumann & Robson de Oliveira Albuquerque & Carlos, 2024. "Application of Non-Parametric and Forecasting Models for the Sustainable Development of Energy Resources in Brazil," Resources, MDPI, vol. 13(11), pages 1-29, October.
  2. Bibi Ibrahim & Luis Rabelo & Alfonso T. Sarmiento & Edgar Gutierrez-Franco, 2023. "A Holistic Approach to Power Systems Using Innovative Machine Learning and System Dynamics," Energies, MDPI, vol. 16(13), pages 1-29, July.
  3. Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).
  4. Liu, Longlong & Zhou, Suyu & Jie, Qian & Du, Pei & Xu, Yan & Wang, Jianzhou, 2024. "A robust time-varying weight combined model for crude oil price forecasting," Energy, Elsevier, vol. 299(C).
  5. Emami Javanmard, M. & Tang, Y. & Wang, Z. & Tontiwachwuthikul, P., 2023. "Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector," Applied Energy, Elsevier, vol. 338(C).
  6. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
  7. Chen, Yunxiao & Lin, Chaojing & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2024. "Day-ahead load forecast based on Conv2D-GRU_SC aimed to adapt to steep changes in load," Energy, Elsevier, vol. 302(C).
  8. Wu, Han & Du, Pei, 2024. "Dual-stream transformer-attention fusion network for short-term carbon price prediction," Energy, Elsevier, vol. 311(C).
  9. Yijue Sun & Fenglin Zhang, 2022. "Grey Multivariable Prediction Model of Energy Consumption with Different Fractional Orders," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
  10. Soto Calvo, Manuel & Lee, Han Soo & Chisale, Sylvester William, 2024. "A novel method for long-term power demand prediction using enhanced data decomposition and neural network with integrated uncertainty analysis: A Cuba case study," Applied Energy, Elsevier, vol. 372(C).
  11. Zhang, Chengyu & Ma, Liangdong & Han, Xing & Zhao, Tianyi, 2024. "Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input and swarm intelligence optimization algorithms," Energy, Elsevier, vol. 288(C).
  12. Wang, Xuerui & Wang, Lin & An, Wuyue, 2024. "Probability density prediction for carbon allowance prices based on TS2Vec and distribution Transformer," Energy Economics, Elsevier, vol. 140(C).
  13. Cheng, Jiyang & Tiwari, Sunil & Khaled, Djebbouri & Mahendru, Mandeep & Shahzad, Umer, 2024. "Forecasting Bitcoin prices using artificial intelligence: Combination of ML, SARIMA, and Facebook Prophet models," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  14. Yuvaraj Natarajan & Sri Preethaa K. R. & Gitanjali Wadhwa & Young Choi & Zengshun Chen & Dong-Eun Lee & Yirong Mi, 2024. "Enhancing Building Energy Efficiency with IoT-Driven Hybrid Deep Learning Models for Accurate Energy Consumption Prediction," Sustainability, MDPI, vol. 16(5), pages 1-23, February.
  15. Wenting Zhao & Haoran Xu & Peng Chen & Juan Zhang & Jing Li & Tingting Cai, 2025. "Elastic Momentum-Enhanced Adaptive Hybrid Method for Short-Term Load Forecasting," Energies, MDPI, vol. 18(13), pages 1-25, June.
  16. 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).
  17. Marian Kampik & Marcin Fice & Adam Pilśniak & Krzysztof Bodzek & Anna Piaskowy, 2023. "An Analysis of Energy Consumption in Small- and Medium-Sized Buildings," Energies, MDPI, vol. 16(3), pages 1-21, February.
  18. Tian, Zhirui & Liu, Weican & Jiang, Wenqian & Wu, Chenye, 2024. "CNNs-Transformer based day-ahead probabilistic load forecasting for weekends with limited data availability," Energy, Elsevier, vol. 293(C).
  19. Xuejun Li & Minghua Jiang & Deyu Cai & Wenqin Song & Yalu Sun, 2024. "A Hybrid Forecasting Model for Electricity Demand in Sustainable Power Systems Based on Support Vector Machine," Energies, MDPI, vol. 17(17), pages 1-16, September.
  20. Mustafa Saglam & Catalina Spataru & Omer Ali Karaman, 2023. "Forecasting Electricity Demand in Turkey Using Optimization and Machine Learning Algorithms," Energies, MDPI, vol. 16(11), pages 1-23, June.
  21. M. K. Islam & N. M. S. Hassan & M. G. Rasul & Kianoush Emami & Ashfaque Ahmed Chowdhury, 2023. "Forecasting of Solar and Wind Resources for Power Generation," Energies, MDPI, vol. 16(17), pages 1-23, August.
  22. Yifei Chen & Zhihan Fu, 2023. "Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
  23. Merve Kayacı Çodur, 2023. "Ensemble Machine Learning Approaches for Prediction of Türkiye’s Energy Demand," Energies, MDPI, vol. 17(1), pages 1-25, December.
  24. Abdil Karakan, 2024. "Predicting Energy Production in Renewable Energy Power Plants Using Deep Learning," Energies, MDPI, vol. 17(16), pages 1-13, August.
  25. Jiao He & Yuhang Li & Xiaochuan Xu & Di Wu, 2025. "Energy consumption forecasting for oil and coal in China based on hybrid deep learning," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-21, January.
  26. Basharat Jamil & Lucía Serrano-Luján, 2024. "Hybrid Metaheuristic Algorithms for Optimization of Countrywide Primary Energy: Analysing Estimation and Year-Ahead Prediction," Energies, MDPI, vol. 17(7), pages 1-26, April.
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