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Building energy performance forecasting: A multiple linear regression approach

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  1. Edgar Segovia & Vladimir Vukovic & Tommaso Bragatto, 2021. "Comparison of Baseline Load Forecasting Methodologies for Active and Reactive Power Demand," Energies, MDPI, vol. 14(22), pages 1-14, November.
  2. Arkar, C. & Žižak, T. & Domjan, S. & Medved, S., 2020. "Dynamic parametric models for the holistic evaluation of semi-transparent photovoltaic/thermal façade with latent storage inserts," Applied Energy, Elsevier, vol. 280(C).
  3. Chen, Sai & Song, Yan & Ding, Yueting & Zhang, Ming & Nie, Rui, 2021. "Using long short-term memory model to study risk assessment and prediction of China’s oil import from the perspective of resilience theory," Energy, Elsevier, vol. 215(PB).
  4. Elsisi, Mahmoud & Amer, Mohammed & Dababat, Alya’ & Su, Chun-Lien, 2023. "A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation," Energy, Elsevier, vol. 281(C).
  5. Joanna Henzel & Łukasz Wróbel & Marcin Fice & Marek Sikora, 2022. "Energy Consumption Forecasting for the Digital-Twin Model of the Building," Energies, MDPI, vol. 15(12), pages 1-21, June.
  6. Lumbreras, Mikel & Garay-Martinez, Roberto & Arregi, Beñat & Martin-Escudero, Koldobika & Diarce, Gonzalo & Raud, Margus & Hagu, Indrek, 2022. "Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters," Energy, Elsevier, vol. 239(PD).
  7. Wang, Qiaochu & Chen, Dongxia & Li, Meijun & Li, Sha & Wang, Fuwei & Yang, Zijie & Zhang, Wanrong & Chen, Shumin & Yao, Dongsheng, 2023. "A novel method for petroleum and natural gas resource potential evaluation and prediction by support vector machines (SVM)," Applied Energy, Elsevier, vol. 351(C).
  8. Massimiliano Manfren & Benedetto Nastasi, 2020. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings," Energies, MDPI, vol. 13(3), pages 1-14, February.
  9. Pedone, Livio & Molaioni, Filippo & Vallati, Andrea & Pampanin, Stefano, 2023. "Energy refurbishment planning of Italian school buildings using data-driven predictive models," Applied Energy, Elsevier, vol. 350(C).
  10. Qingwen, Wang & XiaoHui, Chu & Chao, Yu, 2024. "Modeling of heat gain through green roofs utilizing artificial intelligence techniques," Energy, Elsevier, vol. 303(C).
  11. Kartikay Gupta & Niladri Chatterjee, 2021. "Stocks Recommendation from Large Datasets Using Important Company and Economic Indicators," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 667-689, December.
  12. Nikseresht, Ali & Amindavar, Hamidreza, 2024. "Energy demand forecasting using adaptive ARFIMA based on a novel dynamic structural break detection framework," Applied Energy, Elsevier, vol. 353(PA).
  13. Antonino D’Amico & Domenico Panno & Giuseppina Ciulla & Antonio Messineo, 2020. "Multi-Energy School System for Seasonal Use in the Mediterranean Area," Sustainability, MDPI, vol. 12(20), pages 1-27, October.
  14. Santos-Herrero, J.M. & Lopez-Guede, J.M. & Flores-Abascal, I., 2021. "Modeling, simulation and control tools for nZEB: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
  15. Jiang, Feifeng & Ma, Jun & Li, Zheng & Ding, Yuexiong, 2022. "Prediction of energy use intensity of urban buildings using the semi-supervised deep learning model," Energy, Elsevier, vol. 249(C).
  16. Ole Øiene Smedegård & Thomas Jonsson & Bjørn Aas & Jørn Stene & Laurent Georges & Salvatore Carlucci, 2021. "The Implementation of Multiple Linear Regression for Swimming Pool Facilities: Case Study at Jøa, Norway," Energies, MDPI, vol. 14(16), pages 1-24, August.
  17. Rosa Francesca De Masi & Gerardo Maria Mauro & Silvia Ruggiero & Francesca Villano, 2023. "Predicting Building Energy Demand and Retrofit Potentials Using New Climatic Stress Indices and Curves," Energies, MDPI, vol. 16(16), pages 1-23, August.
  18. Hua, Pengmin & Wang, Haichao & Xie, Zichan & Lahdelma, Risto, 2024. "District heating load patterns and short-term forecasting for buildings and city level," Energy, Elsevier, vol. 289(C).
  19. Feng, Yayuan & Yao, Jian & Li, Zhonghao & Zheng, Rongyue, 2022. "Uncertainty prediction of energy consumption in buildings under stochastic shading adjustment," Energy, Elsevier, vol. 254(PA).
  20. Lu, Hongfang & Cheng, Feifei & Ma, Xin & Hu, Gang, 2020. "Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower," Energy, Elsevier, vol. 203(C).
  21. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  22. Chakraborty, Debaditya & Alam, Arafat & Chaudhuri, Saptarshi & Başağaoğlu, Hakan & Sulbaran, Tulio & Langar, Sandeep, 2021. "Scenario-based prediction of climate change impacts on building cooling energy consumption with explainable artificial intelligence," Applied Energy, Elsevier, vol. 291(C).
  23. Tamer, Tolga & Gürsel Dino, Ipek & Meral Akgül, Cagla, 2022. "Data-driven, long-term prediction of building performance under climate change: Building energy demand and BIPV energy generation analysis across Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
  24. Song, Yang & Peskova, Monika & Rolando, Davide & Zucker, Gerhard & Madani, Hatef, 2023. "Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach," Applied Energy, Elsevier, vol. 352(C).
  25. Sun, Jian & Liu, Gang & Sun, Boyang & Xiao, Gang, 2021. "Light-stacking strengthened fusion based building energy consumption prediction framework via variable weight feature selection," Applied Energy, Elsevier, vol. 303(C).
  26. Shiyi Song & Hong Leng & Ran Guo, 2022. "Multi-Agent-Based Model for the Urban Macro-Level Impact Factors of Building Energy Consumption on Different Types of Land," Land, MDPI, vol. 11(11), pages 1-24, November.
  27. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
  28. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  29. Sahraei, Mohammad Ali & Duman, Hakan & Çodur, Muhammed Yasin & Eyduran, Ecevit, 2021. "Prediction of transportation energy demand: Multivariate Adaptive Regression Splines," Energy, Elsevier, vol. 224(C).
  30. Venkatraj, V. & Dixit, M.K., 2022. "Challenges in implementing data-driven approaches for building life cycle energy assessment: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  31. William Mounter & Chris Ogwumike & Huda Dawood & Nashwan Dawood, 2021. "Machine Learning and Data Segmentation for Building Energy Use Prediction—A Comparative Study," Energies, MDPI, vol. 14(18), pages 1-42, September.
  32. Tamás Mizik & Lajos Nagy & Zoltán Gabnai & Attila Bai, 2020. "The Major Driving Forces of the EU and US Ethanol Markets with Special Attention Paid to the COVID-19 Pandemic," Energies, MDPI, vol. 13(21), pages 1-22, October.
  33. Simon Wenninger & Christian Wiethe, 2021. "Benchmarking Energy Quantification Methods to Predict Heating Energy Performance of Residential Buildings in Germany," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(3), pages 223-242, June.
  34. Lara Ramadan & Isam Shahrour & Hussein Mroueh & Fadi Hage Chehade, 2021. "Use of Machine Learning Methods for Indoor Temperature Forecasting," Future Internet, MDPI, vol. 13(10), pages 1-18, September.
  35. Razak Olu-Ajayi & Hafiz Alaka & Hakeem Owolabi & Lukman Akanbi & Sikiru Ganiyu, 2023. "Data-Driven Tools for Building Energy Consumption Prediction: A Review," Energies, MDPI, vol. 16(6), pages 1-20, March.
  36. 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).
  37. Wenninger, Simon & Kaymakci, Can & Wiethe, Christian, 2022. "Explainable long-term building energy consumption prediction using QLattice," Applied Energy, Elsevier, vol. 308(C).
  38. Somu, Nivethitha & Raman M R, Gauthama & Ramamritham, Krithi, 2021. "A deep learning framework for building energy consumption forecast," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
  39. Leonardo Brain García Fernández & Anna Diva Plasencia Lotufo & Carlos Roberto Minussi, 2023. "Development of a Short-Term Electrical Load Forecasting in Disaggregated Levels Using a Hybrid Modified Fuzzy-ARTMAP Strategy," Energies, MDPI, vol. 16(10), pages 1-30, May.
  40. Hany Habbak & Mohamed Mahmoud & Khaled Metwally & Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Load Forecasting Techniques and Their Applications in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
  41. Shiyi Song & Hong Leng & Han Xu & Ran Guo & Yan Zhao, 2020. "Impact of Urban Morphology and Climate on Heating Energy Consumption of Buildings in Severe Cold Regions," IJERPH, MDPI, vol. 17(22), pages 1-24, November.
  42. Görtz, J. & Jürgensen, J. & Stolz, D. & Wieprecht, S. & Terheiden, K., 2022. "Energy load prediction on structures and buildings-Effect of numerical model complexity on simulation of heat fluxes across the structure/environment interface," Applied Energy, Elsevier, vol. 326(C).
  43. Xiwen Cui & Shaojun E & Dongxiao Niu & Dongyu Wang & Mingyu Li, 2021. "An Improved Forecasting Method and Application of China’s Energy Consumption under the Carbon Peak Target," Sustainability, MDPI, vol. 13(15), pages 1-21, August.
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