1. Predicting energy consumption in Mexico: Integrating environmental, economic, and energy data with machine learning techniques for sustainable development. (2025). Kayae, Altan ; Li, Heng.
   In: Energy.
   RePEc:eee:energy:v:324:y:2025:i:c:s0360544225016342.

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2. An Improved Neural Network Algorithm for Energy Consumption Forecasting. (2024). Tu, Chuang ; Li, Xingyuan ; Ran, Jin ; Wang, Jiahui ; Bai, Jing.
   In: Sustainability.
   RePEc:gam:jsusta:v:16:y:2024:i:21:p:9332-:d:1507743.

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3. Towards energy freedom: Exploring sustainable solutions for energy independence and self-sufficiency using integrated renewable energy-driven hydrogen system. (2024). Yusaf, T ; Laimon, M.
   In: Renewable Energy.
   RePEc:eee:renene:v:222:y:2024:i:c:s0960148124000132.

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4. On the Height of One-Dimensional Random Walk. (2023). Abdelkader, Mohamed.
   In: Mathematics.
   RePEc:gam:jmathe:v:11:y:2023:i:21:p:4513-:d:1272525.

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5. Ensemble Machine Learning Approaches for Prediction of Türkiye’s Energy Demand. (2023). Odur, Merve Kayaci.
   In: Energies.
   RePEc:gam:jeners:v:17:y:2023:i:1:p:74-:d:1305510.

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6. Gross electricity consumption forecasting using LSTM and SARIMA approaches: A case study of Türkiye. (2023). Bilgili, Mehmet ; Pinar, Engin.
   In: Energy.
   RePEc:eee:energy:v:284:y:2023:i:c:s0360544223019692.

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7. A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment. (2023). Zhao, Zhizhen ; Butala, Mark ; Pesantez, Jorge E ; Lee, Christopher ; Li, Binbin ; Stillwell, Ashlynn S.
   In: Energy.
   RePEc:eee:energy:v:283:y:2023:i:c:s0360544223025367.

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8. Development of regression models to forecast the CO2 emissions from fossil fuels in the BRICS and MINT countries. (2023). Karakurt, Izzet ; Aydin, Gokhan.
   In: Energy.
   RePEc:eee:energy:v:263:y:2023:i:pa:s0360544222025361.

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9. Energy Demand of the Road Transport Sector of Saudi Arabia—Application of a Causality-Based Machine Learning Model to Ensure Sustainable Environment. (2022). Rahman, Syed Masiur ; Reshi, Omer ; Kashifi, Mohammad Tamim ; Shafiullah, MD ; Islam, Md Kamrul ; Arifuzzaman, MD ; Hasan, Md Arif ; Al-Ismail, Fahad S ; Gazder, Uneb ; al Mamun, Abdullah ; Mansoor, Umer.
   In: Sustainability.
   RePEc:gam:jsusta:v:14:y:2022:i:23:p:16064-:d:990507.

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10. Electricity Demand Forecasting of Hospital Buildings in Istanbul. (2022). Soyler, Ibrahim ; Izgi, Ercan.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:13:p:8187-:d:855905.

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11. Energy Consumption Forecasting in Korea Using Machine Learning Algorithms. (2022). Shin, Sun-Youn ; Woo, Han-Gyun.
    In: Energies.
    RePEc:gam:jeners:v:15:y:2022:i:13:p:4880-:d:854656.

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12. Forecasting the Olympic medal distribution – A socioeconomic machine learning model. (2022). Schreyer, Dominik ; Schmidt, Sascha L ; Wunderlich, Linus ; Schlembach, Christoph.
    In: Technological Forecasting and Social Change.
    RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521007459.

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13. Potential, trend and economic assessments of global wave power. (2022). Shao, Zhuxiao ; Gao, Huijun ; Lee, Dong Young ; Liang, Bingchen.
    In: Renewable Energy.
    RePEc:eee:renene:v:195:y:2022:i:c:p:1087-1102.

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14. System dynamics modelling to assess the impact of renewable energy systems and energy efficiency on the performance of the energy sector. (2022). Mai, Thanh ; Yusaf, Talal ; Goh, Steven ; Laimon, Mohamd.
    In: Renewable Energy.
    RePEc:eee:renene:v:193:y:2022:i:c:p:1041-1048.

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15. Explaining household electricity consumption using quantile regression, decision tree and artificial neural network. (2022). Nzotcha, Urbain ; Tamo, Thomas T ; Ngohe, Paul Salomon ; Voufo, Joseph ; Kenfack, Joseph ; Nsangou, Jean Calvin.
    In: Energy.
    RePEc:eee:energy:v:250:y:2022:i:c:s0360544222007599.

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16. Another perspective towards energy consumption factors in Pakistan: Fresh policy insights from novel methodological framework. (2022). Alvarado, Rafael ; Akram, Sabahat ; Hussain, Khadim ; Abbasi, Kashif Raza ; Zhang, Jinjun ; Almulhim, Abdulaziz I.
    In: Energy.
    RePEc:eee:energy:v:249:y:2022:i:c:s0360544222006612.

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17. A Data-Driven Multi-Regime Approach for Predicting Energy Consumption. (2021). Kahraman, Muhammet Mustafa ; Kotan, Muhammed ; Kantardzic, Mehmed.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2021:i:20:p:6763-:d:658352.

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18. Modelling and forecasting the oil consumptions of the BRICS-T countries. (2021). Karakurt, Izzet.
    In: Energy.
    RePEc:eee:energy:v:220:y:2021:i:c:s0360544220328279.

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19. The Determinants and Forecasting of Electricity Consumption in Pakistan. (2021). Bibi, Maryam ; Khan, Imran Ali ; Ullah, Hamid ; Wahid, Fazle ; Ali, Abid ; Jan, Sajjad Ahmad.
    In: International Journal of Energy Economics and Policy.
    RePEc:eco:journ2:2021-01-30.

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20. Prediction of household electricity consumption and effectiveness of concerted intervention strategies based on occupant behaviour and personality traits. (2020). Lu, Yujie ; Cui, Qingbin ; Shen, Meng ; Wei, Kua Harn.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:127:y:2020:i:c:s1364032120301337.

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21. Using a temporal input-output approach to analyze the ripple effect of China’s energy consumption. (2020). Huanyu, Ren ; Dong, MU ; Tijun, Fan ; Jianbang, DU ; Yongwei, Cheng.
    In: Energy.
    RePEc:eee:energy:v:211:y:2020:i:c:s0360544220317497.

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22. A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity consumption. (2020). Kaytez, Fazil.
    In: Energy.
    RePEc:eee:energy:v:197:y:2020:i:c:s0360544220303078.

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23. Implications of the Sustainable Development Goals on national energy demand: The case of Indonesia. (2020). Simsek, Yeliz ; Santika, Wayan G ; Urmee, Tania ; Bahri, Parisa A ; Anisuzzaman, M ; Shafiullah, G M.
    In: Energy.
    RePEc:eee:energy:v:196:y:2020:i:c:s0360544220302073.

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24. Daily electrical energy consumption: Periodicity, harmonic regression method and forecasting. (2020). Akdi, Yilmaz ; Okkaolu, Yasin ; Golveren, Elif.
    In: Energy.
    RePEc:eee:energy:v:191:y:2020:i:c:s0360544219322194.

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25. Hybrid modeling in the predictive analytics of energy systems and prices. (2020). Duru, Okan ; Gulay, Emrah.
    In: Applied Energy.
    RePEc:eee:appene:v:268:y:2020:i:c:s0306261920304979.

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26. The Estimation of Turkeys Energy Demand Through Artificial Neural Networks and Support Vector Regression Methods. (2020). Kayaku, Mehmet.
    In: Alphanumeric Journal.
    RePEc:anm:alpnmr:v:8:y:2020:i:2:p:227-236.

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27. Modeling of Energy Consumption Forecast with Economic Indicators Using Particle Swarm Optimization and Genetic Algorithm: An Application in Turkey between 1979 and 2050. (2020). Author-Nameezel, Emre Yakut.
    In: Alphanumeric Journal.
    RePEc:anm:alpnmr:v:8:y:2020:i:1:p:59-78.

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28. Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand. (2019). Shamshirband, Shahaboddin ; Pakseresht, Saeed ; Hafezi, Reza ; Zamani, Mazdak ; Akhavan, Amir Naser.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:21:p:4124-:d:281381.

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29. Factor decomposition of China’s industrial electricity consumption using structural decomposition analysis. (2019). Gao, Yuning ; Zhao, Xintong ; Yu, Miao.
    In: Structural Change and Economic Dynamics.
    RePEc:eee:streco:v:51:y:2019:i:c:p:67-76.

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30. Disaggregating time series on multiple criteria for robust forecasting: The case of long-term electricity demand in Greece. (2019). Siskos, Yannis ; Psarras, John ; Angelopoulos, Dimitrios.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:275:y:2019:i:1:p:252-265.

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31. Electricity Sales Forecasting Using Hybrid Autoregressive Integrated Moving Average and Soft Computing Approaches in the Absence of Explanatory Variables. (2018). Shao, Yuehjen E ; Tsai, Yi-Shan.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:7:p:1848-:d:158021.

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32. Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach. (2018). Begum, Jahitha ; Selvarasan, Iniyan ; Rahman, Habeebur.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:12:p:3442-:d:189135.

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33. Forecasting methods in energy planning models. (2018). Mourshed, Monjur ; Debnath, Kumar Biswajit.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:88:y:2018:i:c:p:297-325.

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34. Automatic generation of models for energy demand estimation using Grammatical Evolution. (2018). Salcedo-Sanz, S ; Colmenar, J M ; Hidalgo, J I.
    In: Energy.
    RePEc:eee:energy:v:164:y:2018:i:c:p:183-193.

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35. A maximum entropy approach to the estimation of spatially and sectorally disaggregated electricity load curves. (2018). Schroder, Thomas ; Tobben, Johannes.
    In: Applied Energy.
    RePEc:eee:appene:v:225:y:2018:i:c:p:797-813.

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36. Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey. (2017). Yumusak, Nejat ; Akpinar, Mustafa ; Adak, Fatih M.
    In: Energies.
    RePEc:gam:jeners:v:10:y:2017:i:6:p:781-:d:100628.

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37. An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan. (2017). Cai, Yanpeng ; Ur, Syed Aziz ; Fazal, Rizwan ; Mirjat, Nayyar Hussain ; Walasai, Gordhan Das.
    In: Energies.
    RePEc:gam:jeners:v:10:y:2017:i:11:p:1868-:d:118909.

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38. A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting. (2017). Shao, Zhen ; Yang, Shan-Lin ; Zhou, Kai-Le ; Chao, FU.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:75:y:2017:i:c:p:123-136.

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39. Modeling household energy expenditure in the United States. (2017). Javid, Roxana J ; Salari, Mahmoud.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:69:y:2017:i:c:p:822-832.

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40. Long-term electrical energy consumption formulating and forecasting via optimized gene expression programming. (2017). , Shr ; Rahim, N A ; Selvaraj, J ; Fallahpour, A.
    In: Energy.
    RePEc:eee:energy:v:126:y:2017:i:c:p:144-164.

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41. The prospects of bioenergy in the future energy system of Inland Norway. (2017). Bolkesjo, Torjus Folsland ; Hagos, Dejene Assefa ; Gebremedhin, Alemayehu.
    In: Energy.
    RePEc:eee:energy:v:121:y:2017:i:c:p:78-91.

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42. Forecasting Regional Electricity Demand for Turkey. (2017). Akarsu, Gulsum.
    In: International Journal of Energy Economics and Policy.
    RePEc:eco:journ2:2017-04-33.

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43. The dynamics of electricity demand in Pakistan: A panel cointegration analysis. (2016). Khan, Muhammad ; Abbas, Faisal.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:65:y:2016:i:c:p:1159-1178.

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44. Probabilistic electric load forecasting: A tutorial review. (2016). Hong, Tao ; Fan, Shu.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:3:p:914-938.

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45. Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey. (2016). Gunay, Merdem .
    In: Energy Policy.
    RePEc:eee:enepol:v:90:y:2016:i:c:p:92-101.

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46. Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study. (2016). Cesarotti, Vittorio ; Introna, Vito ; Benedetti, Miriam ; Serranti, Jacopo .
    In: Applied Energy.
    RePEc:eee:appene:v:165:y:2016:i:c:p:60-71.

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47. A blueprint for an energy policy in Greece with considerations of climate change. (2016). Benekis, Vasilis ; Chatzizacharia, Kalliopi ; Hatziavramidis, Dimitris .
    In: Applied Energy.
    RePEc:eee:appene:v:162:y:2016:i:c:p:382-389.

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48. Nonlinear production path and an alternative reserves estimate for South Asian natural gas. (2015). Guseo, Renato ; Darda, Md Abud ; Mortarino, Cinzia.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:47:y:2015:i:c:p:654-664.

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49. Can China achieve its carbon intensity target by 2020 while sustaining economic growth?. (2015). Wei, Yi-Ming ; Chevallier, Julien ; Wang, Ping ; Zhu, Bangzhu.
    In: Ecological Economics.
    RePEc:eee:ecolec:v:119:y:2015:i:c:p:209-216.

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50. A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables. (2015). Muttaqi, K. M. ; Vu, D. H. ; Agalgaonkar, A. P..
    In: Applied Energy.
    RePEc:eee:appene:v:140:y:2015:i:c:p:385-394.

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51. Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections. (2014). Aydin, Gokhan.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:35:y:2014:i:c:p:382-389.

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52. Review of energy models to the development of an efficient industrial energy model. (2014). Olanrewaju, O. A, ; Jimoh, A. A, .
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:30:y:2014:i:c:p:661-671.

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53. Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm. (2014). Dede, Tayfun ; Kankal, Murat ; Uzlu, Ergun ; Akpnar, Adem .
    In: Energy.
    RePEc:eee:energy:v:75:y:2014:i:c:p:295-303.

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54. An estimation model for determining the annual energy cost budget in educational facilities using SARIMA (seasonal autoregressive integrated moving average) and ANN (artificial neural network). (2014). Hong, Taehoon ; Jeong, Kwangbok ; Koo, Choongwan.
    In: Energy.
    RePEc:eee:energy:v:71:y:2014:i:c:p:71-79.

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55. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey. (2014). Nacar, Sinan ; Kankal, Murat ; ozturk, Hasan Tahsin ; Uzlu, Ergun ; Akpnar, Adem .
    In: Energy.
    RePEc:eee:energy:v:69:y:2014:i:c:p:638-647.

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56. Modeling and forecasting of cooling and electricity load demand. (2014). Lu, Y. ; Jafari, M. A. ; Brouwer, J. ; Bisse, Emmanuel ; Vaghefi, A..
    In: Applied Energy.
    RePEc:eee:appene:v:136:y:2014:i:c:p:186-196.

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57. A proposal for a site location planning model of environmentally friendly urban energy supply plants using an environment and energy geographical information system (E-GIS) database (DB) and an artificial neural network (ANN). (2014). Yee, Jurng-Jae ; Yeo, In-Ae.
    In: Applied Energy.
    RePEc:eee:appene:v:119:y:2014:i:c:p:99-117.

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58. A Forecasting Model for Thailand€™s Unemployment Rate. (2013). Chutiman, Nipaporn ; Mahipan, Kanlapat ; Kumphon, Bungon.
    In: Modern Applied Science.
    RePEc:ibn:masjnl:v:7:y:2013:i:7:p:10.

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59. Vision 2023: Forecasting Turkeys natural gas demand between 2013 and 2030. (2013). Melikoglu, Mehmet.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:22:y:2013:i:c:p:393-400.

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60. Vision 2023: Assessing the feasibility of electricity and biogas production from municipal solid waste in Turkey. (2013). Melikoglu, Mehmet.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:19:y:2013:i:c:p:52-63.

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61. A grey-forecasting interval-parameter mixed-integer programming approach for integrated electric-environmental management–A case study of Beijing. (2013). Cai, Yanpeng ; Wang, Xingwei ; Chen, Jiajun ; Dai, Chao.
    In: Energy.
    RePEc:eee:energy:v:63:y:2013:i:c:p:334-344.

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62. Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas. (2013). Wu, Zhibin ; Xu, Jiuping.
    In: Energy.
    RePEc:eee:energy:v:49:y:2013:i:c:p:19-31.

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63. Estimation of electrical power consumption in subway station design by intelligent approach. (2013). Leung, Philip C. M., ; Lee, Eric W. M., .
    In: Applied Energy.
    RePEc:eee:appene:v:101:y:2013:i:c:p:634-643.

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64. A new hybrid day-ahead peak load forecasting method for Iran’s National Grid. (2013). Hooshmand, R. ; Moazzami, M. ; Khodabakhshian, A..
    In: Applied Energy.
    RePEc:eee:appene:v:101:y:2013:i:c:p:489-501.

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65. Energy models for demand forecasting—A review. (2012). Suganthi, L. ; Samuel, Anand A..
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:16:y:2012:i:2:p:1223-1240.

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66. A decision support model for reducing electric energy consumption in elementary school facilities. (2012). Hong, Taehoon ; Jeong, Kwangbok ; Koo, Choongwan.
    In: Applied Energy.
    RePEc:eee:appene:v:95:y:2012:i:c:p:253-266.

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67. Transport energy demand modeling of South Korea using artificial neural network. (2011). Geem, Zong Woo.
    In: Energy Policy.
    RePEc:eee:enepol:v:39:y:2011:i:8:p:4644-4650.

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68. 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. (2011). Nadimi, V. ; Asadzadeh, S. M. ; Sheikalishahi, M. ; Saberi, M. ; Tajvidi, A. ; Azadeh, A..
    In: Applied Energy.
    RePEc:eee:appene:v:88:y:2011:i:11:p:3850-3859.

    Full description at Econpapers || Download paper

1. Abdel-Aal, R.E. ; Al-Garni, A.Z. Forecasting monthly electric energy consumption in Eastern Saudi Arabia using univariate time-series analysis. 1997 Energy. 22 1059-1069

2. Akay, D. ; Atak, M. Grey prediction with rolling mechanism for electricity demand forecasting of Turkey. 2007 Energy. 32 1670-1675

3. Altinay, G. ; Karagöl, E. Structural break, unit root, and the causality between energy consumption and GDP in Turkey. 2004 Energy Econ. 26 985-994

4. Ãœnler, A. Improvement of energy demand forecasts using swarm intelligence: the case of Turkey with projections to 2025. 2008 Energy Policy. 36 1937-1944

5. Azadeh, A. ; Ghaderi, S.F. ; Sohrabkhani, S. A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran. 2008 Energy Policy. 36 2637-2644

6. Bianco, V. ; Manca, O. ; Nardini, S. Electricity consumption forecasting in Italy using linear regression models. 2009 Energy. 34 1413-1421

7. Bianco, V. ; Manca, O. ; Nardini, S. ; Minea, A.A. Analysis and forecasting of nonresidential electricity consumption in Romania. 2010 Appl Energy. 87 3584-3590

8. Canyurt, O.E. ; Ceylan, H. ; Ozturk, H.K. ; Hepbasli, A. Energy demand estimation based on two-different genetic algorithm approaches. 2004 Energy Sources. 26 1313-1320
   Paper not yet in RePEc: Add citation now
   
9. Center for Economics and Personal Finance Education (CEPFE). Macroeconomic concepts. The College of Business of New Mexico State University; 2009. <http://cepfe.nmsu.edu/?q=book/print/12>.
   Paper not yet in RePEc: Add citation now
   

10. Ceylan, H. ; Ceylan, H. ; Haldenbilen, S. ; Baskan, O. Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey. 2008 Energy Policy. 36 2527-2537

11. Ceylan, H. ; Ozturk, H.K. Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach. 2004 Energy Convers Manage. 45 2525-2537
    Paper not yet in RePEc: Add citation now
    
12. Ceylan, H. ; Ozturk, H.K. ; Hepbasli, A. ; Utlu, Z. Estimating energy and exergy production and consumption values using three different genetic algorithm approaches, part 2: application and scenarios. 2005 Energy Sources. 27 629-639
    Paper not yet in RePEc: Add citation now
    

13. Chang, C.C. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China. 2010 Appl Energy. 87 3533-3537

14. Dahl, C.A. ; Mcdonald, L. Forecasting energy demand in the developing world. 1998 Energy Sources A: Recov, Util, Environ Effects. 20 875-889
    Paper not yet in RePEc: Add citation now
    

15. Dincer, I. ; Dost, S. Energy intensities for Canada. 1996 Appl Energy. 76 207-211

16. Ediger, V.Åž. ; Akar, S. ARIMA forecasting of primary energy demand by fuel in Turkey. 2007 Energy Policy. 35 1701-1708

17. Ediger, V.Åž. ; Akar, S. ; UÄŸurlu, B. Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model. 2006 Energy Policy. 34 3836-3846

18. Ediger, V.S. ; Tatlidil, H. Forecasting the primary-energy demand in Turkey and analysis of cyclic patterns. 2002 Energy Convers Manage. 43 473-487
    Paper not yet in RePEc: Add citation now
    

19. Egelioglu, F. ; Mohamad, A.A. ; Guven, H. Economic variables and electricity consumption in Northern Cyprus. 2001 Energy. 26 355-362

20. Ekonomou, L. Greek long-term energy consumption prediction using artificial neural network. 2010 Energy. 35 512-517

21. ErdoÄŸdu, E. Electricity demand analysis using cointegration and ARIMA modelling: a case study of Turkey. 2007 Energy Policy. 35 1129-1146

22. Fausett, L. Fundamentals of neural networks. 1994 Prentice-Hall: New Jersey
    Paper not yet in RePEc: Add citation now
    

23. Geem, Z.W. ; Roper, W.E. Energy demand estimation of South Korea using artificial neural network. 2009 Energy Policy. 37 4049-4054

24. Glasure, Y.U. ; Lee, A.R. Cointegration, error-correction, and the relationship between GDP and electricity: the case of South Korea and Singapore. 1997 Resour Energy Econ. 20 17-25

25. Halıcı U. Artificial neural network. Lecture notes. Ankara: Middle East Technical University; 2001. <http://vision1.eee.metu.edu.tr./~halici/543LectureNotes/543index.html>.
    Paper not yet in RePEc: Add citation now
    

26. Haldenbilen, S. ; Ceylan, H. Genetic algorithm approach to estimate transport energy demand in Turkey. 2005 Energy Policy. 33 89-98

27. Hamzaçebi, C. Forecasting of Turkey’s net electricity energy consumption on sectoral bases. 2007 Energy Policy. 35 2009-2016
    Paper not yet in RePEc: Add citation now
    

28. Jebaraj, S. ; Iniyan, S. A review of energy models. 2006 Renew Sustain Energy Rev. 10 281-311

29. Jinke, L. ; Hualing, S. ; Dianming, G. Causality relationship between coal consumption and GDP: difference of major OECD and non-OECD countries. 2008 Appl Energy. 85 421-429

30. Kılıç, F.C. ; Kaya, D. Energy production, consumption, policies, and recent developments in Turkey. 2007 Renew Sustain Energy Rev. 11 1312-1320

31. Kang, J.Y. ; Song, J.H. Neural networks applications in determining the fatigue crack opening load. 1997 Int J Fatigue. 20 57-69
    Paper not yet in RePEc: Add citation now
    
32. Kavaklioglu, K. ; Ceylan, H. ; Ozturk, H.K. ; Canyurt, O.E. Modeling and prediction of Turkey’s electricity consumption using artificial neural networks. 2009 Energy Convers Manage. 50 2719-2727
    Paper not yet in RePEc: Add citation now
    

33. Lise, W. ; Montfort, K.V. Energy consumption and GDP in Turkey: is there a co-integration relationship?. 2007 Energy Econ. 29 1166-1178

34. Ministry of Energy and Natural Resources (MENR). Energy sources, Ankara, Turkey; 2009. <http://www.enerji.gov.tr/tr/inc_enerji.php>.
    Paper not yet in RePEc: Add citation now
    
35. Ministry of Energy and Natural Resources (MENR). Primary energy sources consumption, Ankara, Turkey; 2009. <http://www.enerji.gov.tr/EKLENTI_VIEW/index.php/raporlar/raporVeriGir/4314/2>.
    Paper not yet in RePEc: Add citation now
    

36. Mohamed, Z. ; Bodger, P. Forecasting electricity consumption in New Zealand using economic and demographic variables. 2005 Energy. 30 1833-1843

37. Mozumder, P. ; Marathe, A. Causality relationship between electricity consumption and GDP in Bangladesh. 2007 Energy Policy. 35 395-402

38. Murat, Y.S. ; Ceylan, H. Use of artificial neural networks for transport energy demand modeling. 2006 Energy Policy. 34 3165-3172

39. Narayan, P.K. ; Narayan, S. ; Popp, S. Does electricity consumption panel Granger cause GDP? A new global evidence. 2010 Appl Energy. 87 3294-3298

40. Narayan, P.K. ; Narayan, S. ; Popp, S. Energy consumption at the state level: the unit root null hypothesis from Australia. 2010 Appl Energy. 87 1953-1962

41. Narayan, P.K. ; Smyth, R. Electricity consumption, employment, and real income in Australia evidence from multivariate Granger causality tests. 2005 Energy Policy. 33 1109-1116

42. Nasr, G.E. ; Badr, E.A. ; Younes, M.R. Neural networks in forecasting electrical energy consumption: univariate and multivariate approaches. 2002 Int J Energy Res. 26 67-78
    Paper not yet in RePEc: Add citation now
    
43. Ozsahin, T.S. ; Birinci, A. ; Cakıroğlu, A.O. Prediction of contact lengths between an elastic layer and two elastic circular punches with neural networks. 2004 Struct Eng Mech. 18 441-459
    Paper not yet in RePEc: Add citation now
    
44. Ozsahin, T.S. ; Oruc, S. Neural network model for resilient modulus of emulsified asphalt mixtures. 2008 Constr Build Mater. 22 1436-1445
    Paper not yet in RePEc: Add citation now
    
45. Ozturk, H.K. ; Canyurt, O.E. ; Hepbaslı, A. ; Utlu, Z. Residential–commercial energy-input estimation based on genetic algorithm (GA) approaches: an application for Turkey. 2004 Energy Build. 36 175-183
    Paper not yet in RePEc: Add citation now
    

46. Ozturk, H.K. ; Ceylan, H. ; Canyurt, O.E. ; Hepbasli, A. Electricity estimation using genetic algorithm approach: a case study of Turkey. 2005 Energy. 30 1003-1012

47. Ozturk, I. ; Acaravci, A. The causal relationship between energy consumption and GDP in Albania, Bulgaria, Hungary and Romania: evidence from ARDL bound testing approach. 2010 Appl Energy. 87 1938-1943

48. Pao, H.T. Comparing linear and nonlinear forecasts for Taiwan’s electricity consumption. 2006 Energy. 31 2129-2141

49. Ranjan, M. ; Jain, V.K. Modeling of electrical energy consumption in Delhi. 1999 Energy (Oxford). 24 351-361

50. Sözen, A. Future projection of the energy dependency of Turkey using artificial neural network. 2009 Energy Policy. 37 4827-4833
    Paper not yet in RePEc: Add citation now
    
51. Sözen, A. ; Akçayol, M.A. ; Arcaklıoğlu, E. Forecasting net energy consumption using artificial neural network. 2006 Energy Sources, B: Econ, Plann, Policy. 1 147-155
    Paper not yet in RePEc: Add citation now
    

52. Sözen, A. ; Arcaklioğlu, E. ; Özkaymak, M. Turkey’s net energy consumption. 2005 Appl Energy. 81 209-221

53. Sözen, A. ; Arcaklioglu, E. Prediction of net energy consumption based on economic indicators (GNP and GDP) in Turkey. 2007 Energy Policy. 35 4981-4992

54. Sözen, A. ; Arcaklioglu, E. Prospects for future projections of the basic energy sources in Turkey. 2007 Energy Sources, B: Econ, Plann, Policy. 2 183-201
    Paper not yet in RePEc: Add citation now
    
55. Sözen, A. ; Gülseven, Z. ; Arcaklioğlu, E. Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies. 2007 Energy Policy. 35 6491-6505
    Paper not yet in RePEc: Add citation now
    

56. Say, N.P. ; Yücel, M. Energy consumption and CO2 emissions in Turkey: empirical analysis and future projection based on an economic growth. 2006 Energy Policy. 34 3870-3876

57. Soytaş U, Sarı R, Özdemir O. Energy consumption and GDP relation in Turkey: a cointegration and vector error correction analysis. In: Economies and business in transition: facilitating competitiveness and change in the global environment proceedings. Global Business and Technology Association; 2001. p. 838–44.
    Paper not yet in RePEc: Add citation now
    

58. Soytas, U. ; Sari, R. Energy consumption and GDP: causality relationship in G-7 countries and emerging markets. 2003 Energy Econ. 25 33-37

59. Sozen, A. ; Arcaklioglu, E. ; Ozkaymak, M. Modeling of the Turkey’s net energy consumption using artificial neural network. 2005 Int J Comput Appl Technol. 22 130-136
    Paper not yet in RePEc: Add citation now
    

60. Toksari, M.D. Ant colony optimization approach to estimate energy demand of Turkey. 2007 Energy Policy. 35 3984-3990

61. Turkish Statistical Institute (TURKSTAT). Foreign trade statistics, Ankara, Turkey; 2010. <http://www.tuik.gov.tr/VeriBilgi.do?tb_id=12&ust_id=4>.
    Paper not yet in RePEc: Add citation now
    
62. Turkish Statistical Institute (TURKSTAT). Population projections and estimations, mid-year population estimation, Ankara, Turkey; 2009. <http://www.tuik.gov.tr/VeriBilgi.do?tb_id=39&ust_id=11>.
    Paper not yet in RePEc: Add citation now
    
63. Turkish Statistical Institute (TURKSTAT). Statistical tables. Employment by years and sex, Ankara, Turkey; 2009. <http://www.tuik.gov.tr/VeriBilgi.do?tb_id=25&ust_id=8>.
    Paper not yet in RePEc: Add citation now
    
64. UÄŸur A. Neural networks. Lecture notes. Ä°zmir: Ege University; 2006. <http://yzgrafik.ege.edu.tr/~aybars/CGAI/NNLectureNotes/YSA.pdf>.
    Paper not yet in RePEc: Add citation now
    

65. Yang, H.Y. A note on the causal relationship between electricity and GDP in Taiwan. 2000 Energy Econ. 22 309-317

66. Yumurtaci, Z. ; Asmaz, E. Electric energy demand of Turkey for the year 2050. 2004 Energy Sources. 26 1157-1164
    Paper not yet in RePEc: Add citation now
    

67. Zhou, P. ; Ang, B.W. ; Poh, K.L. A trigonometric grey prediction approach to forecasting electricity demand. 2006 Energy. 31 2839-2847

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   In: Energy & Environment.
   RePEc:sae:engenv:v:35:y:2024:i:3:p:1493-1531.

   Full description at Econpapers || Download paper

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   RePEc:eee:energy:v:286:y:2024:i:c:s0360544223029602.

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   In: Sustainability.
   RePEc:gam:jsusta:v:15:y:2023:i:22:p:16102-:d:1283439.

   Full description at Econpapers || Download paper

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   In: Future Internet.
   RePEc:gam:jftint:v:15:y:2023:i:4:p:134-:d:1112675.

   Full description at Econpapers || Download paper

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   In: Energies.
   RePEc:gam:jeners:v:16:y:2023:i:4:p:2035-:d:1073156.

   Full description at Econpapers || Download paper

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   In: Energies.
   RePEc:gam:jeners:v:16:y:2023:i:18:p:6675-:d:1242158.

   Full description at Econpapers || Download paper

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   In: Energies.
   RePEc:gam:jeners:v:15:y:2022:i:9:p:3425-:d:810446.

   Full description at Econpapers || Download paper

8. Analysis of time series models for Brazilian electricity demand forecasting. (2022). Castro, Victor F ; Zocatelli, Matheus ; Velasquez, Carlos E.
   In: Energy.
   RePEc:eee:energy:v:247:y:2022:i:c:s0360544222003863.

   Full description at Econpapers || Download paper

9. Modeling and Forecasting Medium-Term Electricity Consumption Using Component Estimation Technique. (2020). Ali, Sajid ; Shah, Ismail ; Iftikhar, Hasnain.
   In: Forecasting.
   RePEc:gam:jforec:v:2:y:2020:i:2:p:9-179:d:362019.

   Full description at Econpapers || Download paper

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    In: Energies.
    RePEc:gam:jeners:v:13:y:2020:i:9:p:2317-:d:354789.

    Full description at Econpapers || Download paper

11. Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis. (2020). Tassinari, P ; Gholami, M ; Torreggiani, D ; Barbaresi, A.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:132:y:2020:i:c:s1364032120303270.

    Full description at Econpapers || Download paper

12. Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts. (2020). Ahmad, Tanveer ; Zhang, Hongcai.
    In: Energy.
    RePEc:eee:energy:v:209:y:2020:i:c:s0360544220315851.

    Full description at Econpapers || Download paper

13. Hybrid modeling in the predictive analytics of energy systems and prices. (2020). Duru, Okan ; Gulay, Emrah.
    In: Applied Energy.
    RePEc:eee:appene:v:268:y:2020:i:c:s0306261920304979.

    Full description at Econpapers || Download paper

14. Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia. (2019). Ni, Kailai ; Wang, Jianzhou ; Tang, Guangyu ; Wei, Danxiang.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:13:p:2467-:d:243188.

    Full description at Econpapers || Download paper

15. A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings. (2019). Torres, Miguel Garcia ; Vazquez, Jose Luis ; Gomez, Francisco A ; Divina, Federico.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:10:p:1934-:d:232835.

    Full description at Econpapers || Download paper

16. Assessing the accuracy of electricity production forecasts in developing countries. (2019). Steinbuks, Jevgenijs.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:3:p:1175-1185.

    Full description at Econpapers || Download paper

17. Bridging the electricity demand and supply gap using dynamic modeling in the Indian context. (2019). Sushil, Professor ; Varma, Rashmi.
    In: Energy Policy.
    RePEc:eee:enepol:v:132:y:2019:i:c:p:515-535.

    Full description at Econpapers || Download paper

18. Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network. (2019). He, Yaoyao ; Qin, Yang ; Wang, XU.
    In: Applied Energy.
    RePEc:eee:appene:v:233-234:y:2019:i::p:565-575.

    Full description at Econpapers || Download paper

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    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:7:p:1687-:d:154918.

    Full description at Econpapers || Download paper

20. Forecasting methods in energy planning models. (2018). Mourshed, Monjur ; Debnath, Kumar Biswajit.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:88:y:2018:i:c:p:297-325.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:144:y:2018:i:c:p:776-788.

    Full description at Econpapers || Download paper

22. A review on time series forecasting techniques for building energy consumption. (2017). Lee, Siew Eang ; Shah, Kwok Wei ; Yang, Junjing ; Zhang, Fan ; Deb, Chirag.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:74:y:2017:i:c:p:902-924.

    Full description at Econpapers || Download paper

23. Energy model – A tool for preventing energy dysfunction. (2017). Laha, Priyanka ; Chakraborty, Basab.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:73:y:2017:i:c:p:95-114.

    Full description at Econpapers || Download paper

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    In: Resources, Conservation & Recycling.
    RePEc:eee:recore:v:123:y:2017:i:c:p:200-207.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:116:y:2016:i:p1:p:1031-1038.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:115:y:2016:i:p1:p:734-745.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:114:y:2016:i:c:p:344-359.

    Full description at Econpapers || Download paper

28. Modelling and predicting electricity consumption in Spain using the stochastic Gamma diffusion process with exogenous factors. (2016). el Hachimi, S ; Gutierrez-Sanchez, R ; Ramos-Abalos, E ; Nafidi, A.
    In: Energy.
    RePEc:eee:energy:v:113:y:2016:i:c:p:309-318.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:109:y:2016:i:c:p:420-429.

    Full description at Econpapers || Download paper

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    In: Energy.
    RePEc:eee:energy:v:100:y:2016:i:c:p:384-390.

    Full description at Econpapers || Download paper

31. Modelling residential electricity demand in the GCC countries. (2016). Hunt, Lester ; Atalla, Tarek N.
    In: Energy Economics.
    RePEc:eee:eneeco:v:59:y:2016:i:c:p:149-158.

    Full description at Econpapers || Download paper

32. Economic Growth and Electricity Consumption in GCC and MENA Countries. (2015). Bildirici, Melike ; Kayiki, Fazil.
    In: South African Journal of Economics.
    RePEc:bla:sajeco:v:83:y:2015:i:2:p:303-316.

    Full description at Econpapers || Download paper

33. Energy consumption projection of Nepal: An econometric approach. (2014). Dalgaard, Tommy ; Parajuli, Ranjan ; Ostergaard, Poul Alberg ; Pokharel, Govind Raj .
    In: Renewable Energy.
    RePEc:eee:renene:v:63:y:2014:i:c:p:432-444.

    Full description at Econpapers || Download paper

34. Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model. (2014). Zhao, Weigang ; Wang, Jianzhou ; Lu, Haiyan.
    In: Omega.
    RePEc:eee:jomega:v:45:y:2014:i:c:p:80-91.

    Full description at Econpapers || Download paper

35. Energy models for demand forecasting—A review. (2012). Suganthi, L. ; Samuel, Anand A..
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:16:y:2012:i:2:p:1223-1240.

    Full description at Econpapers || Download paper

36. Development of benchmark models for the Egyptian residential buildings sector. (2012). Attia, Shady ; Gratia, Elisabeth ; Evrard, Arnaud .
    In: Applied Energy.
    RePEc:eee:appene:v:94:y:2012:i:c:p:270-284.

    Full description at Econpapers || Download paper

37. A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting. (2012). Yu, Lean ; Li, jianping ; Wang, Shuai ; Tang, Ling.
    In: Applied Energy.
    RePEc:eee:appene:v:93:y:2012:i:c:p:432-443.

    Full description at Econpapers || Download paper

38. Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm. (2011). Hong, Wei-Chiang.
    In: Energy.
    RePEc:eee:energy:v:36:y:2011:i:9:p:5568-5578.

    Full description at Econpapers || Download paper

39. A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China. (2011). Yu, Lean ; Wang, Shuai ; Tang, Ling.
    In: Energy.
    RePEc:eee:energy:v:36:y:2011:i:11:p:6542-6554.

    Full description at Econpapers || Download paper

40. Modeling and forecasting of Turkeys energy consumption using socio-economic and demographic variables. (2011). zsahin, Talat Sukru ; Kankal, Murat ; Komurcu, Murat Ihsan ; Akpinar, Adem.
    In: Applied Energy.
    RePEc:eee:appene:v:88:y:2011:i:5:p:1927-1939.

    Full description at Econpapers || Download paper

41. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models. (2010). Nabney, Ian T. ; Nguyen, Hang T..
    In: Energy.
    RePEc:eee:energy:v:35:y:2010:i:9:p:3674-3685.

    Full description at Econpapers || Download paper

42. An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran. (2010). Seraj, O. ; Saberi, M. ; Azadeh, A..
    In: Energy.
    RePEc:eee:energy:v:35:y:2010:i:6:p:2351-2366.

    Full description at Econpapers || Download paper

43. Analysis and forecasting of nonresidential electricity consumption in Romania. (2010). Bianco, Vincenzo ; Nardini, Sergio ; Manca, Oronzio ; Minea, Alina A..
    In: Applied Energy.
    RePEc:eee:appene:v:87:y:2010:i:11:p:3584-3590.

    Full description at Econpapers || Download paper

44. Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks. (2009). Shaahid, S. M. ; Abdel-Aal, R. E. ; Elhadidy, M. A..
    In: Renewable Energy.
    RePEc:eee:renene:v:34:y:2009:i:7:p:1686-1699.

    Full description at Econpapers || Download paper

45. Electricity consumption forecasting in Italy using linear regression models. (2009). Bianco, Vincenzo ; Nardini, Sergio ; Manca, Oronzio.
    In: Energy.
    RePEc:eee:energy:v:34:y:2009:i:9:p:1413-1421.

    Full description at Econpapers || Download paper

46. Forecasting the transport energy demand based on PLSR method in China. (2009). Ning, Yadong ; Zhang, Ming ; Mu, Hailin ; Li, Gang.
    In: Energy.
    RePEc:eee:energy:v:34:y:2009:i:9:p:1396-1400.

    Full description at Econpapers || Download paper

47. A review of energy models. (2006). Jebaraj, S. ; Iniyan, S..
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:10:y:2006:i:4:p:281-311.

    Full description at Econpapers || Download paper

48. A trigonometric grey prediction approach to forecasting electricity demand. (2006). Zhou, Peng ; Ang, B.W. ; Poh, K. L..
    In: Energy.
    RePEc:eee:energy:v:31:y:2006:i:14:p:2839-2847.

    Full description at Econpapers || Download paper

49. Economic variables and electricity consumption in Northern Cyprus. (2001). Guven, H. ; Egelioglu, F. ; Mohamad, A. A..
    In: Energy.
    RePEc:eee:energy:v:26:y:2001:i:4:p:355-362.

    Full description at Econpapers || Download paper

50. Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon. (2001). Saab, Samer ; Nasr, George ; Badr, Elie .
    In: Energy.
    RePEc:eee:energy:v:26:y:2001:i:1:p:1-14.

    Full description at Econpapers || Download paper

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