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Forecasting of energy production and consumption in Asturias (northern Spain)

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  1. Lowry, Gordon & Bianeyin, Felix U. & Shah, Nirav, 2007. "Seasonal autoregressive modelling of water and fuel consumptions in buildings," Applied Energy, Elsevier, vol. 84(5), pages 542-552, May.
  2. Bufalo, Michele & Orlando, Giuseppe, 2023. "A three-factor stochastic model for forecasting production of energy materials," Finance Research Letters, Elsevier, vol. 51(C).
  3. Neto, João C. do L. & da Costa Junior, Carlos T. & Bitar, Sandro D.B. & Junior, Walter B., 2011. "Forecasting of energy and diesel consumption and the cost of energy production in isolated electrical systems in the Amazon using a fuzzification process in time series models," Energy Policy, Elsevier, vol. 39(9), pages 4947-4955, September.
  4. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
  5. Tsai, Bi-Huei & Chang, Chih-Jen & Chang, Chun-Hsien, 2016. "Elucidating the consumption and CO2 emissions of fossil fuels and low-carbon energy in the United States using Lotka–Volterra models," Energy, Elsevier, vol. 100(C), pages 416-424.
  6. Sun-Youn Shin & Han-Gyun Woo, 2022. "Energy Consumption Forecasting in Korea Using Machine Learning Algorithms," Energies, MDPI, vol. 15(13), pages 1-20, July.
  7. Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng, 2016. "Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model," Energy, Elsevier, vol. 100(C), pages 384-390.
  8. Ediger, Volkan S. & Akar, Sertac & Ugurlu, Berkin, 2006. "Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model," Energy Policy, Elsevier, vol. 34(18), pages 3836-3846, December.
  9. Zhang, Wen Yu & Hong, Wei-Chiang & Dong, Yucheng & Tsai, Gary & Sung, Jing-Tian & Fan, Guo-feng, 2012. "Application of SVR with chaotic GASA algorithm in cyclic electric load forecasting," Energy, Elsevier, vol. 45(1), pages 850-858.
  10. Kumar, Ujjwal & Jain, V.K., 2010. "Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India," Energy, Elsevier, vol. 35(4), pages 1709-1716.
  11. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
  12. Adom, Philip Kofi & Bekoe, William, 2013. "Modelling electricity demand in Ghana revisited: The role of policy regime changes," Energy Policy, Elsevier, vol. 61(C), pages 42-50.
  13. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
  14. Rallapalli, Srinivasa Rao & Ghosh, Sajal, 2012. "Forecasting monthly peak demand of electricity in India—A critique," Energy Policy, Elsevier, vol. 45(C), pages 516-520.
  15. de Oliveira, Erick Meira & Cyrino Oliveira, Fernando Luiz, 2018. "Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods," Energy, Elsevier, vol. 144(C), pages 776-788.
  16. Akdi, Yılmaz & Gölveren, Elif & Okkaoğlu, Yasin, 2020. "Daily electrical energy consumption: Periodicity, harmonic regression method and forecasting," Energy, Elsevier, vol. 191(C).
  17. Azadeh, A. & Asadzadeh, S.M. & Ghanbari, A., 2010. "An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments," Energy Policy, Elsevier, vol. 38(3), pages 1529-1536, March.
  18. Pin Li & Jin-Suo Zhang, 2018. "A New Hybrid Method for China’s Energy Supply Security Forecasting Based on ARIMA and XGBoost," Energies, MDPI, vol. 11(7), pages 1-28, June.
  19. Sajal Ghosh & Anjana Das, 2002. "Short-run electricity demand forecasts in Maharashtra," Applied Economics, Taylor & Francis Journals, vol. 34(8), pages 1055-1059.
  20. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  21. Ediger, Volkan S. & Akar, Sertac, 2007. "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, Elsevier, vol. 35(3), pages 1701-1708, March.
  22. Paredes-Sánchez, José P. & García-Elcoro, Víctor E. & Rosillo-Calle, Frank & Xiberta-Bernat, Jorge, 2016. "Assessment of forest bioenergy potential in a coal-producing area in Asturias (Spain) and recommendations for setting up a Biomass Logistic Centre (BLC)," Applied Energy, Elsevier, vol. 171(C), pages 133-141.
  23. Shoaib Ahmed Khatri & Nayyar Hussain Mirjat & Khanji Harijan & Mohammad Aslam Uqaili & Syed Feroz Shah & Pervez Hameed Shaikh & Laveet Kumar, 2022. "An Overview of the Current Energy Situation of Pakistan and the Way Forward towards Green Energy Implementation," Energies, MDPI, vol. 16(1), pages 1-27, December.
  24. Hong, Wei-Chiang, 2011. "Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm," Energy, Elsevier, vol. 36(9), pages 5568-5578.
  25. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
  26. Azadeh, A. & Asadzadeh, S.M. & Saberi, M. & Nadimi, V. & Tajvidi, A. & Sheikalishahi, M., 2011. "A Neuro-fuzzy-stochastic frontier analysis approach for long-term natural gas consumption forecasting and behavior analysis: The cases of Bahrain, Saudi Arabia, Syria, and UAE," Applied Energy, Elsevier, vol. 88(11), pages 3850-3859.
  27. Rae-Jun Park & Kyung-Bin Song & Bo-Sung Kwon, 2020. "Short-Term Load Forecasting Algorithm Using a Similar Day Selection Method Based on Reinforcement Learning," Energies, MDPI, vol. 13(10), pages 1-19, May.
  28. Xi Zhang & Zheng Li & Linwei Ma & Chinhao Chong & Weidou Ni, 2019. "Forecasting the Energy Embodied in Construction Services Based on a Combination of Static and Dynamic Hybrid Input-Output Models," Energies, MDPI, vol. 12(2), pages 1-26, January.
  29. Bhandari, Ramchandra & Subedi, Subodh, 2023. "Evaluation of surplus hydroelectricity potential in Nepal until 2040 and its use for hydrogen production via electrolysis," Renewable Energy, Elsevier, vol. 212(C), pages 403-414.
  30. Montoya, Francisco G. & Montoya, Maria G. & Gómez, Julio & Manzano-Agugliaro, Francisco & Alameda-Hernández, Enrique, 2014. "The research on energy in spain: A scientometric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 173-183.
  31. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
  32. Azadeh, A. & Asadzadeh, S.M. & Mirseraji, G.H. & Saberi, M., 2015. "An emotional learning-neuro-fuzzy inference approach for optimum training and forecasting of gas consumption estimation models with cognitive data," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 47-63.
  33. Laha, Priyanka & Chakraborty, Basab, 2017. "Energy model – A tool for preventing energy dysfunction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 95-114.
  34. Suat Ozturk & Feride Ozturk, 2018. "Forecasting Energy Consumption of Turkey by Arima Model," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 8(2), pages 52-60, February.
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