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Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025

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  1. Ardakani, F.J. & Ardehali, M.M., 2014. "Long-term electrical energy consumption forecasting for developing and developed economies based on different optimized models and historical data types," Energy, Elsevier, vol. 65(C), pages 452-461.
  2. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
  3. Emre Yakut & Ezel Özkan, 2020. "Modeling of Energy Consumption Forecast with Economic Indicators Using Particle Swarm Optimization and Genetic Algorithm: An Application in Turkey between 1979 and 2050," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 8(1), pages 59-78, June.
  4. Morgan Bazilian & Patrick Nussbaumer & Hans-Holger Rogner & Abeeku Brew-Hammond & Vivien Foster & Shonali Pachauri & Eric Williams & Mark Howells & Philippe Niyongabo & Lawrence Musaba & Brian Ó Galla, 2011. "Energy Access Scenarios to 2030 for the Power Sector in Sub-Saharan Africa," Working Papers 2011.68, Fondazione Eni Enrico Mattei.
  5. Tutun, Salih & Chou, Chun-An & Canıyılmaz, Erdal, 2015. "A new forecasting framework for volatile behavior in net electricity consumption: A case study in Turkey," Energy, Elsevier, vol. 93(P2), pages 2406-2422.
  6. Shaikh, Mohammad A. & Kucukvar, Murat & Onat, Nuri Cihat & Kirkil, Gokhan, 2017. "A framework for water and carbon footprint analysis of national electricity production scenarios," Energy, Elsevier, vol. 139(C), pages 406-421.
  7. 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.
  8. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2012. "A PSO–GA optimal model to estimate primary energy demand of China," Energy Policy, Elsevier, vol. 42(C), pages 329-340.
  9. Elsland, Rainer & Divrak, Can & Fleiter, Tobias & Wietschel, Martin, 2014. "Turkey’s Strategic Energy Efficiency Plan – An ex ante impact assessment of the residential sector," Energy Policy, Elsevier, vol. 70(C), pages 14-29.
  10. Colmenar, J.M. & Hidalgo, J.I. & Salcedo-Sanz, S., 2018. "Automatic generation of models for energy demand estimation using Grammatical Evolution," Energy, Elsevier, vol. 164(C), pages 183-193.
  11. Atul Anand & L Suganthi, 2018. "Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand," Energies, MDPI, vol. 11(4), pages 1-15, March.
  12. Yujing Liu & Ruoyun Du & Dongxiao Niu, 2022. "Forecast of Coal Demand in Shanxi Province Based on GA—LSSVM under Multiple Scenarios," Energies, MDPI, vol. 15(17), pages 1-16, September.
  13. Reza Mikaeil & Sina Shaffiee Haghshenas & Zoheir Sedaghati, 2019. "Geotechnical risk evaluation of tunneling projects using optimization techniques (case study: the second part of Emamzade Hashem tunnel)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 1099-1113, July.
  14. Assareh, E. & Behrang, M.A. & Assari, M.R. & Ghanbarzadeh, A., 2010. "Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran," Energy, Elsevier, vol. 35(12), pages 5223-5229.
  15. Yu, Shi-wei & Zhu, Ke-jun, 2012. "A hybrid procedure for energy demand forecasting in China," Energy, Elsevier, vol. 37(1), pages 396-404.
  16. Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2015. "A comparative study on prediction methods for China's medium- and long-term coal demand," Energy, Elsevier, vol. 93(P2), pages 1671-1683.
  17. Swasti R. Khuntia & Jose L. Rueda & Mart A.M.M. Van der Meijden, 2018. "Long-Term Electricity Load Forecasting Considering Volatility Using Multiplicative Error Model," Energies, MDPI, vol. 11(12), pages 1-19, November.
  18. 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).
  19. Melikoglu, Mehmet, 2013. "Hydropower in Turkey: Analysis in the view of Vision 2023," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 503-510.
  20. Kaboli, S. Hr. Aghay & Selvaraj, J. & Rahim, N.A., 2016. "Long-term electric energy consumption forecasting via artificial cooperative search algorithm," Energy, Elsevier, vol. 115(P1), pages 857-871.
  21. Sonmez, Mustafa & Akgüngör, Ali Payıdar & Bektaş, Salih, 2017. "Estimating transportation energy demand in Turkey using the artificial bee colony algorithm," Energy, Elsevier, vol. 122(C), pages 301-310.
  22. Reza Darisavi Bahmanshir & Ali Akbar Naji Meidani & Mahdi Khodaparast Mashhadi & Narges Salehnia, 2018. "Reversibility Test of Oil Demand Function of OECD Countries Importing Oil from Iran with an Emphasis on Technological and Environmental Considerations: Symmetric and Asymmetric Models," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 132-139.
  23. Erdogdu, Erkan, 2010. "Natural gas demand in Turkey," Applied Energy, Elsevier, vol. 87(1), pages 211-219, January.
  24. Jun Hao & Xiaolei Sun & Qianqian Feng, 2020. "A Novel Ensemble Approach for the Forecasting of Energy Demand Based on the Artificial Bee Colony Algorithm," Energies, MDPI, vol. 13(3), pages 1-25, January.
  25. Hakan HOTUNLUOGLU & Etem KARAKAYA, 2011. "Forecasting Turkey’s Energy Demand Using Artificial Neural Networks: Three Scenario Applications," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 11(Special I), pages 87-94.
  26. Kialashaki, Arash & Reisel, John R., 2014. "Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States," Energy, Elsevier, vol. 76(C), pages 749-760.
  27. Behrang, M.A. & Assareh, E. & Ghalambaz, M. & Assari, M.R. & Noghrehabadi, A.R., 2011. "Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm)," Energy, Elsevier, vol. 36(9), pages 5649-5654.
  28. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
  29. Hafezi, Reza & Akhavan, AmirNaser & Pakseresht, Saeed & A. Wood, David, 2021. "Global natural gas demand to 2025: A learning scenario development model," Energy, Elsevier, vol. 224(C).
  30. Zeng, Yu-Rong & Zeng, Yi & Choi, Beomjin & Wang, Lin, 2017. "Multifactor-influenced energy consumption forecasting using enhanced back-propagation neural network," Energy, Elsevier, vol. 127(C), pages 381-396.
  31. Reza Hafezi & Amir Naser Akhavan & Mazdak Zamani & Saeed Pakseresht & Shahaboddin Shamshirband, 2019. "Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand," Energies, MDPI, vol. 12(21), pages 1-22, October.
  32. Rafael Sánchez-Durán & Julio Barbancho & Joaquín Luque, 2019. "Solar Energy Production for a Decarbonization Scenario in Spain," Sustainability, MDPI, vol. 11(24), pages 1-29, December.
  33. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.
  34. Alexander Melnik & Irina Naoumova & Kirill Ermolaev & Jerome Katrichis, 2021. "Driving Innovation through Energy Efficiency: A Russian Regional Analysis," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
  35. Yuan, Xiao-Chen & Sun, Xun & Zhao, Weigang & Mi, Zhifu & Wang, Bing & Wei, Yi-Ming, 2017. "Forecasting China’s regional energy demand by 2030: A Bayesian approach," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 85-95.
  36. Kaboli, S. Hr. Aghay & Fallahpour, A. & Selvaraj, J. & Rahim, N.A., 2017. "Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming," Energy, Elsevier, vol. 126(C), pages 144-164.
  37. Mahdis sadat Jalaee & Alireza Shakibaei & Amin GhasemiNejad & Sayyed Abdolmajid Jalaee & Reza Derakhshani, 2021. "A Novel Computational Intelligence Approach for Coal Consumption Forecasting in Iran," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
  38. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
  39. Yu, Lean & Zhao, Yaqing & Tang, Ling & Yang, Zebin, 2019. "Online big data-driven oil consumption forecasting with Google trends," International Journal of Forecasting, Elsevier, vol. 35(1), pages 213-223.
  40. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden & Tomasz Rokicki, 2022. "The Role of Renewable Energy Sources in Electricity Production in Poland and the Background of Energy Policy of the European Union at the Beginning of the COVID-19 Crisis," Energies, MDPI, vol. 15(22), pages 1-17, November.
  41. Fan, Jie & Wang, Qiang & Sun, Wei, 2015. "The failure of China׳s Energy Development Strategy 2050 and its impact on carbon emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1160-1170.
  42. Atul Anand & L. Suganthi, 2017. "Forecasting of Electricity Demand by Hybrid ANN-PSO Models," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 6(4), pages 66-83, October.
  43. Alireza Pourdaryaei & Mohammad Mohammadi & Mazaher Karimi & Hazlie Mokhlis & Hazlee A. Illias & Seyed Hamidreza Aghay Kaboli & Shameem Ahmad, 2021. "Recent Development in Electricity Price Forecasting Based on Computational Intelligence Techniques in Deregulated Power Market," Energies, MDPI, vol. 14(19), pages 1-28, September.
  44. Narimani, Mohammad Rasoul & Azizipanah-Abarghooee, Rasoul & Zoghdar-Moghadam-Shahrekohne, Behrouz & Gholami, Kayvan, 2013. "A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type," Energy, Elsevier, vol. 49(C), pages 119-136.
  45. Uzlu, Ergun & Kankal, Murat & Akpınar, Adem & Dede, Tayfun, 2014. "Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm," Energy, Elsevier, vol. 75(C), pages 295-303.
  46. Gouveia, João Pedro & Fortes, Patrícia & Seixas, Júlia, 2012. "Projections of energy services demand for residential buildings: Insights from a bottom-up methodology," Energy, Elsevier, vol. 47(1), pages 430-442.
  47. Karadede, Yusuf & Ozdemir, Gultekin & Aydemir, Erdal, 2017. "Breeder hybrid algorithm approach for natural gas demand forecasting model," Energy, Elsevier, vol. 141(C), pages 1269-1284.
  48. Sahraei, Mohammad Ali & Çodur, Merve Kayaci, 2022. "Prediction of transportation energy demand by novel hybrid meta-heuristic ANN," Energy, Elsevier, vol. 249(C).
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