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Modelling and forecasting monthly electric energy consumption in eastern Saudi Arabia using abductive networks
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- Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
- Egelioglu, F. & Mohamad, A.A. & Guven, H., 2001. "Economic variables and electricity consumption in Northern Cyprus," Energy, Elsevier, vol. 26(4), pages 355-362.
- Attia, Shady & Evrard, Arnaud & Gratia, Elisabeth, 2012. "Development of benchmark models for the Egyptian residential buildings sector," Applied Energy, Elsevier, vol. 94(C), pages 270-284.
- Konstantinos Papageorgiou & Elpiniki I. Papageorgiou & Katarzyna Poczeta & Dionysis Bochtis & George Stamoulis, 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 13(9), pages 1-32, May.
- 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.
- Fazıl Kayıkçı & Melike Bildirici, 2015. "Economic Growth and Electricity Consumption in GCC and MENA Countries," South African Journal of Economics, Economic Society of South Africa, vol. 83(2), pages 303-316, June.
- Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio & Minea, Alina A., 2010. "Analysis and forecasting of nonresidential electricity consumption in Romania," Applied Energy, Elsevier, vol. 87(11), pages 3584-3590, November.
- Zhang, Ming & Mu, Hailin & Li, Gang & Ning, Yadong, 2009. "Forecasting the transport energy demand based on PLSR method in China," Energy, Elsevier, vol. 34(9), pages 1396-1400.
- Wang, Guimei & Mukhtar, Azfarizal & Moayedi, Hossein & Khalilpoor, Nima & Tt, Quynh, 2024. "Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector," Energy, Elsevier, vol. 298(C).
- Varma, Rashmi & Sushil,, 2019. "Bridging the electricity demand and supply gap using dynamic modeling in the Indian context," Energy Policy, Elsevier, vol. 132(C), pages 515-535.
- 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.
- Gulay, Emrah & Sen, Mustafa & Akgun, Omer Burak, 2024. "Forecasting electricity production from various energy sources in Türkiye: A predictive analysis of time series, deep learning, and hybrid models," Energy, Elsevier, vol. 286(C).
- Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.
- Parajuli, Ranjan & Østergaard, Poul Alberg & Dalgaard, Tommy & Pokharel, Govind Raj, 2014. "Energy consumption projection of Nepal: An econometric approach," Renewable Energy, Elsevier, vol. 63(C), pages 432-444.
- Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
- Abdel-Aal, R.E. & Elhadidy, M.A. & Shaahid, S.M., 2009. "Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks," Renewable Energy, Elsevier, vol. 34(7), pages 1686-1699.
- Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
- Saab, Samer & Badr, Elie & Nasr, George, 2001. "Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon," Energy, Elsevier, vol. 26(1), pages 1-14.
- Zhao, Weigang & Wang, Jianzhou & Lu, Haiyan, 2014. "Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model," Omega, Elsevier, vol. 45(C), pages 80-91.
- Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
- 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.
- Azadeh, A. & Saberi, M. & Seraj, O., 2010. "An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran," Energy, Elsevier, vol. 35(6), pages 2351-2366.
- Wang, Shuai & Yu, Lean & Tang, Ling & Wang, Shouyang, 2011. "A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China," Energy, Elsevier, vol. 36(11), pages 6542-6554.
- 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.
- Deb, Chirag & Zhang, Fan & Yang, Junjing & Lee, Siew Eang & Shah, Kwok Wei, 2017. "A review on time series forecasting techniques for building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 902-924.
- Ahmad, Tanveer & Zhang, Hongcai, 2020. "Novel deep supervised ML models with feature selection approach for large-scale utilities and buildings short and medium-term load requirement forecasts," Energy, Elsevier, vol. 209(C).
- Tang, Ling & Yu, Lean & Wang, Shuai & Li, Jianping & Wang, Shouyang, 2012. "A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting," Applied Energy, Elsevier, vol. 93(C), pages 432-443.
- 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.
- Federico Divina & Miguel García Torres & Francisco A. Goméz Vela & José Luis Vázquez Noguera, 2019. "A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings," Energies, MDPI, vol. 12(10), pages 1-23, May.
- Velasquez, Carlos E. & Zocatelli, Matheus & Estanislau, Fidellis B.G.L. & Castro, Victor F., 2022. "Analysis of time series models for Brazilian electricity demand forecasting," Energy, Elsevier, vol. 247(C).
- Cao, Guohua & Wu, Lijuan, 2016. "Support vector regression with fruit fly optimization algorithm for seasonal electricity consumption forecasting," Energy, Elsevier, vol. 115(P1), pages 734-745.
- Dahiru A Bala & Mohammed Shuaibu, 2024. "Forecasting United Kingdom's energy consumption using machine learning and hybrid approaches," Energy & Environment, , vol. 35(3), pages 1493-1531, May.
- Zhang, Wenbin & Tian, Lixin & Wang, Minggang & Zhen, Zaili & Fang, Guochang, 2016. "The evolution model of electricity market on the stable development in China and its dynamic analysis," Energy, Elsevier, vol. 114(C), pages 344-359.
- Salma Hamad Almuhaini & Nahid Sultana, 2023. "Forecasting Long-Term Electricity Consumption in Saudi Arabia Based on Statistical and Machine Learning Algorithms to Enhance Electric Power Supply Management," Energies, MDPI, vol. 16(4), pages 1-28, February.
- 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).
- Kailai Ni & Jianzhou Wang & Guangyu Tang & Danxiang Wei, 2019. "Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia," Energies, MDPI, vol. 12(13), pages 1-30, June.
- Nafidi, A. & Gutiérrez, R. & Gutiérrez-Sánchez, R. & Ramos-Ábalos, E. & El Hachimi, S., 2016. "Modelling and predicting electricity consumption in Spain using the stochastic Gamma diffusion process with exogenous factors," Energy, Elsevier, vol. 113(C), pages 309-318.
- 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.
- Zhou, Dengji & Yu, Ziqiang & Zhang, Huisheng & Weng, Shilie, 2016. "A novel grey prognostic model based on Markov process and grey incidence analysis for energy conversion equipment degradation," Energy, Elsevier, vol. 109(C), pages 420-429.
- Son, Hyojoo & Kim, Changwan, 2017. "Short-term forecasting of electricity demand for the residential sector using weather and social variables," Resources, Conservation & Recycling, Elsevier, vol. 123(C), pages 200-207.
- Hasnain Iftikhar & Josue E. Turpo-Chaparro & Paulo Canas Rodrigues & Javier Linkolk López-Gonzales, 2023. "Day-Ahead Electricity Demand Forecasting Using a Novel Decomposition Combination Method," Energies, MDPI, vol. 16(18), pages 1-22, September.
- 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.
- Ismail Shah & Hasnain Iftikhar & Sajid Ali, 2020. "Modeling and Forecasting Medium-Term Electricity Consumption Using Component Estimation Technique," Forecasting, MDPI, vol. 2(2), pages 1-17, May.
- Abhishek Kashyap & Om Ji Shukla & Bal Krishna Jha & Bharti Ramtiyal & Gunjan Soni, 2023. "Enhancing Sustainable Dairy Industry Growth through Cold-Supply-Chain-Integrated Production Forecasting," Sustainability, MDPI, vol. 15(22), pages 1-17, November.
- Ahmad Taha & Basel Barakat & Mohammad M. A. Taha & Mahmoud A. Shawky & Chun Sing Lai & Sajjad Hussain & Muhammad Zainul Abideen & Qammer H. Abbasi, 2023. "A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset," Future Internet, MDPI, vol. 15(4), pages 1-17, March.
- Nahid Sultana & S. M. Zakir Hossain & Salma Hamad Almuhaini & Dilek Düştegör, 2022. "Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand," Energies, MDPI, vol. 15(9), pages 1-26, May.
- He, Yaoyao & Qin, Yang & Wang, Shuo & Wang, Xu & Wang, Chao, 2019. "Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network," Applied Energy, Elsevier, vol. 233, pages 565-575.
- Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
- Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "A trigonometric grey prediction approach to forecasting electricity demand," Energy, Elsevier, vol. 31(14), pages 2839-2847.
- 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.
- Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.