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A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables

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Cited by:

  1. Javid, Roxana J. & Nejat, Ali, 2017. "A comprehensive model of regional electric vehicle adoption and penetration," Transport Policy, Elsevier, vol. 54(C), pages 30-42.
  2. Asif Reza Anik & Sanzidur Rahman, 2021. "Commercial Energy Demand Forecasting in Bangladesh," Energies, MDPI, vol. 14(19), pages 1-22, October.
  3. Best, Rohan, 2022. "Energy inequity variation across contexts," Applied Energy, Elsevier, vol. 309(C).
  4. Syed Muhammad Raza Abidi & Mushtaq Hussain & Yonglin Xu & Wu Zhang, 2018. "Prediction of Confusion Attempting Algebra Homework in an Intelligent Tutoring System through Machine Learning Techniques for Educational Sustainable Development," Sustainability, MDPI, vol. 11(1), pages 1-21, December.
  5. Tian, Wei & Heo, Yeonsook & de Wilde, Pieter & Li, Zhanyong & Yan, Da & Park, Cheol Soo & Feng, Xiaohang & Augenbroe, Godfried, 2018. "A review of uncertainty analysis in building energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 285-301.
  6. Shen, Meng & Lu, Yujie & Wei, Kua Harn & Cui, Qingbin, 2020. "Prediction of household electricity consumption and effectiveness of concerted intervention strategies based on occupant behaviour and personality traits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
  7. Yongquan Dong & Zichen Zhang & Wei-Chiang Hong, 2018. "A Hybrid Seasonal Mechanism with a Chaotic Cuckoo Search Algorithm with a Support Vector Regression Model for Electric Load Forecasting," Energies, MDPI, vol. 11(4), pages 1-21, April.
  8. Lu Gan & Yuanyuan Wang & Yusheng Wang & Benjamin Lev & Wenjing Shen & Wen Jiang, 2021. "Coupling coordination analysis with data-driven technology for disaster–economy–ecology system: an empirical study in China," 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. 107(3), pages 2123-2153, July.
  9. Tian, Ye & Li, Yudi & Sun, Jian & Ye, Jianhong, 2021. "Characterizing favored users of incentive-based traffic demand management program," Transport Policy, Elsevier, vol. 105(C), pages 94-102.
  10. Hoxha, Julian & Çodur, Muhammed Yasin & Mustafaraj, Enea & Kanj, Hassan & El Masri, Ali, 2023. "Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis," Applied Energy, Elsevier, vol. 350(C).
  11. Jin, Haowei & Guo, Jue & Tang, Lei & Du, Pei, 2024. "Long-term electricity demand forecasting under low-carbon energy transition: Based on the bidirectional feedback between power demand and generation mix," Energy, Elsevier, vol. 286(C).
  12. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
  13. Yaquelin Verenice Pantoja-Pacheco & Armando Javier Ríos-Lira & José Antonio Vázquez-López & José Alfredo Jiménez-García & Martha Laura Asato-España & Moisés Tapia-Esquivias, 2021. "One Note for Fractionation and Increase for Mixed-Level Designs When the Levels Are Not Multiple," Mathematics, MDPI, vol. 9(13), pages 1-20, June.
  14. Nahyun Kwon & Kwonsik Song & Moonseo Park & Youjin Jang & Inseok Yoon & Yonghan Ahn, 2019. "Preliminary Service Life Estimation Model for MEP Components Using Case-Based Reasoning and Genetic Algorithm," Sustainability, MDPI, vol. 11(11), pages 1-17, May.
  15. Liu, Xiaomei & Li, Sihan & Gao, Meina, 2024. "A discrete time-varying grey Fourier model with fractional order terms for electricity consumption forecast," Energy, Elsevier, vol. 296(C).
  16. Radhakrishnan Angamuthu Chinnathambi & Anupam Mukherjee & Mitch Campion & Hossein Salehfar & Timothy M. Hansen & Jeremy Lin & Prakash Ranganathan, 2018. "A Multi-Stage Price Forecasting Model for Day-Ahead Electricity Markets," Forecasting, MDPI, vol. 1(1), pages 1-21, July.
  17. Mushtaq Hussain Khan & Hina Yaqub Bhatti & Arshad Hassan & Ahmad Fraz, 2021. "The diversification–performance nexus: mediating role of information asymmetry," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(3), pages 787-810, September.
  18. Sholeh Hadi Pramono & Mahdin Rohmatillah & Eka Maulana & Rini Nur Hasanah & Fakhriy Hario, 2019. "Deep Learning-Based Short-Term Load Forecasting for Supporting Demand Response Program in Hybrid Energy System," Energies, MDPI, vol. 12(17), pages 1-16, August.
  19. Cheng-Wen Lee & Bing-Yi Lin, 2016. "Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting," Energies, MDPI, vol. 9(11), pages 1-16, October.
  20. Cheng-Wen Lee & Bing-Yi Lin, 2017. "Applications of the Chaotic Quantum Genetic Algorithm with Support Vector Regression in Load Forecasting," Energies, MDPI, vol. 10(11), pages 1-18, November.
  21. Wang, Endong & Alp, Neslihan & Shi, Jonathan & Wang, Chao & Zhang, Xiaodong & Chen, Hong, 2017. "Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting," Energy, Elsevier, vol. 125(C), pages 197-210.
  22. Warut Pannakkong & Thanyaporn Harncharnchai & Jirachai Buddhakulsomsiri, 2022. "Forecasting Daily Electricity Consumption in Thailand Using Regression, Artificial Neural Network, Support Vector Machine, and Hybrid Models," Energies, MDPI, vol. 15(9), pages 1-21, April.
  23. Marwen Elkamel & Lily Schleider & Eduardo L. Pasiliao & Ali Diabat & Qipeng P. Zheng, 2020. "Long-Term Electricity Demand Prediction via Socioeconomic Factors—A Machine Learning Approach with Florida as a Case Study," Energies, MDPI, vol. 13(15), pages 1-21, August.
  24. Sojin Park & Nahyun Kwon & Yonghan Ahn, 2019. "Forecasting Repair Schedule for Building Components Based on Case-Based Reasoning and Fuzzy-AHP," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
  25. Carolina Deina & João Lucas Ferreira dos Santos & Lucas Henrique Biuk & Mauro Lizot & Attilio Converti & Hugo Valadares Siqueira & Flavio Trojan, 2023. "Forecasting Electricity Demand by Neural Networks and Definition of Inputs by Multi-Criteria Analysis," Energies, MDPI, vol. 16(4), pages 1-24, February.
  26. Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
  27. 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.
  28. Liu, Xue & Ding, Yong & Tang, Hao & Fan, Lingxiao & Lv, Jie, 2022. "Investigating the effects of key drivers on energy consumption of nonresidential buildings: A data-driven approach integrating regularization and quantile regression," Energy, Elsevier, vol. 244(PA).
  29. Luo, Na & Langevin, Jared & Chandra-Putra, Handi & Lee, Sang Hoon, 2022. "Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling," Applied Energy, Elsevier, vol. 309(C).
  30. Wei-Chiang Hong & Guo-Feng Fan, 2019. "Hybrid Empirical Mode Decomposition with Support Vector Regression Model for Short Term Load Forecasting," Energies, MDPI, vol. 12(6), pages 1-16, March.
  31. Ahmed, T. & Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2018. "Load forecasting under changing climatic conditions for the city of Sydney, Australia," Energy, Elsevier, vol. 142(C), pages 911-919.
  32. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
  33. Xie, Xiangmin & Chen, Daolian, 2022. "Data-driven dynamic harmonic model for modern household appliances," Applied Energy, Elsevier, vol. 312(C).
  34. Mao, Hui & Shi, Chaoqian & Tang, Heyan & Lu, Yufeng, 2024. "Time preferences and energy consumption of rural household in China," Energy Economics, Elsevier, vol. 132(C).
  35. Yani Lian & Jungang Luo & Wei Xue & Ganggang Zuo & Shangyao Zhang, 2022. "Cause-driven Streamflow Forecasting Framework Based on Linear Correlation Reconstruction and Long Short-term Memory," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1661-1678, March.
  36. Majid Mohammady, 2023. "Badland erosion susceptibility mapping using machine learning data mining techniques, Firozkuh watershed, Iran," 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. 117(1), pages 703-721, May.
  37. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
  38. Moustris, K. & Kavadias, K.A. & Zafirakis, D. & Kaldellis, J.K., 2020. "Medium, short and very short-term prognosis of load demand for the Greek Island of Tilos using artificial neural networks and human thermal comfort-discomfort biometeorological data," Renewable Energy, Elsevier, vol. 147(P1), pages 100-109.
  39. Zou, Guojian & Lai, Ziliang & Li, Ye & Liu, Xinghua & Li, Wenxiang, 2022. "Exploring the nonlinear impact of air pollution on housing prices: A machine learning approach," Economics of Transportation, Elsevier, vol. 31(C).
  40. Li, Bo & Ding, Junqi & Wang, Jieqiong & Zhang, Biao & Zhang, Lingxian, 2021. "Key factors affecting the adoption willingness, behavior, and willingness-behavior consistency of farmers regarding photovoltaic agriculture in China," Energy Policy, Elsevier, vol. 149(C).
  41. Kaneko, Nanae & Fujimoto, Yu & Kabe, Satoshi & Hayashida, Motonari & Hayashi, Yasuhiro, 2020. "Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand," Applied Energy, Elsevier, vol. 265(C).
  42. Raza, Muhammad Qamar & Nadarajah, Mithulananthan & Ekanayake, Chandima, 2017. "Demand forecast of PV integrated bioclimatic buildings using ensemble framework," Applied Energy, Elsevier, vol. 208(C), pages 1626-1638.
  43. Yuhan Zhang & Youqi Wang & Yiru Bai & Ruiyuan Zhang & Xu Liu & Xian Ma, 2023. "Prediction of Spatial Distribution of Soil Organic Carbon in Helan Farmland Based on Different Prediction Models," Land, MDPI, vol. 12(11), pages 1-15, October.
  44. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
  45. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
  46. Cai, Zhen & Xie, Yi & Aguilar, Francisco X., 2017. "Eco-label credibility and retailer effects on green product purchasing intentions," Forest Policy and Economics, Elsevier, vol. 80(C), pages 200-208.
  47. Bharat Prasad Bhandari & Subodh Dhakal & Ching-Ying Tsou, 2024. "Assessing the Prediction Accuracy of Frequency Ratio, Weight of Evidence, Shannon Entropy, and Information Value Methods for Landslide Susceptibility in the Siwalik Hills of Nepal," Sustainability, MDPI, vol. 16(5), pages 1-25, March.
  48. Yuanyuan Zhou & Min Zhou & Qing Xia & Wei-Chiang Hong, 2019. "Construction of EMD-SVR-QGA Model for Electricity Consumption: Case of University Dormitory," Mathematics, MDPI, vol. 7(12), pages 1-23, December.
  49. Lawal, Abiola S. & Servadio, Joseph L. & Davis, Tate & Ramaswami, Anu & Botchwey, Nisha & Russell, Armistead G., 2021. "Orthogonalization and machine learning methods for residential energy estimation with social and economic indicators," Applied Energy, Elsevier, vol. 283(C).
  50. Zhen Li & Yanbin Li & Shuangshuang Shao, 2019. "Analysis of Influencing Factors and Trend Forecast of Carbon Emission from Energy Consumption in China Based on Expanded STIRPAT Model," Energies, MDPI, vol. 12(16), pages 1-14, August.
  51. Kibria, Abu S.M.G. & Costanza, Robert & Gasparatos, Alexandros & Soto, José, 2022. "A composite human wellbeing index for ecosystem-dependent communities: A case study in the Sundarbans, Bangladesh," Ecosystem Services, Elsevier, vol. 53(C).
  52. 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.
  53. Changrui Deng & Xiaoyuan Zhang & Yanmei Huang & Yukun Bao, 2021. "Equipping Seasonal Exponential Smoothing Models with Particle Swarm Optimization Algorithm for Electricity Consumption Forecasting," Energies, MDPI, vol. 14(13), pages 1-14, July.
  54. Kibria, Abu S.M.G. & Costanza, Robert & Groves, Colin & Behie, Alison M., 2018. "The interactions between livelihood capitals and access of local communities to the forest provisioning services of the Sundarbans Mangrove Forest, Bangladesh," Ecosystem Services, Elsevier, vol. 32(PA), pages 41-49.
  55. Capozzoli, Alfonso & Piscitelli, Marco Savino & Neri, Francesco & Grassi, Daniele & Serale, Gianluca, 2016. "A novel methodology for energy performance benchmarking of buildings by means of Linear Mixed Effect Model: The case of space and DHW heating of out-patient Healthcare Centres," Applied Energy, Elsevier, vol. 171(C), pages 592-607.
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