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Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy

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  1. Wang, Yuhao & Qu, Ke & Chen, Xiangjie & Zhang, Xingxing & Riffat, Saffa, 2022. "Holistic electrification vs deep energy retrofits for optimal decarbonisation pathways of UK dwellings: A case study of the 1940s’ British post-war masonry house," Energy, Elsevier, vol. 241(C).
  2. J. R. S. Iruela & L. G. B. Ruiz & M. I. Capel & M. C. Pegalajar, 2021. "A TensorFlow Approach to Data Analysis for Time Series Forecasting in the Energy-Efficiency Realm," Energies, MDPI, vol. 14(13), pages 1-22, July.
  3. Salvia, Monica & Simoes, Sofia G. & Herrando, María & Čavar, Marko & Cosmi, Carmelina & Pietrapertosa, Filomena & Gouveia, João Pedro & Fueyo, Norberto & Gómez, Antonio & Papadopoulou, Kiki & Taxeri, , 2021. "Improving policy making and strategic planning competencies of public authorities in the energy management of municipal public buildings: The PrioritEE toolbox and its application in five mediterranea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  4. Quan, Steven Jige & Xue, Yang & Li, Chaosu, 2025. "Nonlinearity in the relationships between urban form and residential energy use intensity," Applied Energy, Elsevier, vol. 383(C).
  5. Aurora Greta Ruggeri & Laura Gabrielli & Massimiliano Scarpa, 2020. "Energy Retrofit in European Building Portfolios: A Review of Five Key Aspects," Sustainability, MDPI, vol. 12(18), pages 1-38, September.
  6. Mahmoud Abdelkader Bashery Abbass & Mohamed Hamdy, 2021. "A Generic Pipeline for Machine Learning Users in Energy and Buildings Domain," Energies, MDPI, vol. 14(17), pages 1-30, August.
  7. Boni Sena & Sheikh Ahmad Zaki & Hom Bahadur Rijal & Jorge Alfredo Ardila-Rey & Nelidya Md Yusoff & Fitri Yakub & Farah Liana & Mohamad Zaki Hassan, 2021. "Development of an Electrical Energy Consumption Model for Malaysian Households, Based on Techno-Socioeconomic Determinant Factors," Sustainability, MDPI, vol. 13(23), pages 1-22, November.
  8. Grillone, Benedetto & Danov, Stoyan & Sumper, Andreas & Cipriano, Jordi & Mor, Gerard, 2020. "A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  9. Beccali, M. & Bonomolo, M. & Ciulla, G. & Lo Brano, V., 2018. "Assessment of indoor illuminance and study on best photosensors' position for design and commissioning of Daylight Linked Control systems. A new method based on artificial neural networks," Energy, Elsevier, vol. 154(C), pages 466-476.
  10. Maria Mrówczyńska & Marta Skiba & Anna Bazan-Krzywoszańska & Dorota Bazuń & Mariusz Kwiatkowski, 2018. "Social and Infrastructural Conditioning of Lowering Energy Costs and Improving the Energy Efficiency of Buildings in the Context of the Local Energy Policy," Energies, MDPI, vol. 11(9), pages 1-16, September.
  11. Seyedzadeh, Saleh & Pour Rahimian, Farzad & Oliver, Stephen & Rodriguez, Sergio & Glesk, Ivan, 2020. "Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making," Applied Energy, Elsevier, vol. 279(C).
  12. Zhouchen Zhang & Jian Yao & Rongyue Zheng, 2024. "Multi-Objective Optimization of Building Energy Saving Based on the Randomness of Energy-Related Occupant Behavior," Sustainability, MDPI, vol. 16(5), pages 1-20, February.
  13. Qi Dong & Kai Xing & Hongrui Zhang, 2017. "Artificial Neural Network for Assessment of Energy Consumption and Cost for Cross Laminated Timber Office Building in Severe Cold Regions," Sustainability, MDPI, vol. 10(1), pages 1-15, December.
  14. Amira Mouakher & Wissem Inoubli & Chahinez Ounoughi & Andrea Ko, 2022. "Expect : EXplainable Prediction Model for Energy ConsumpTion," Mathematics, MDPI, vol. 10(2), pages 1-21, January.
  15. Soutullo, S. & Giancola, E. & Heras, M.R., 2018. "Dynamic energy assessment to analyze different refurbishment strategies of existing dwellings placed in Madrid," Energy, Elsevier, vol. 152(C), pages 1011-1023.
  16. Ciulla, G. & D'Amico, A. & Lo Brano, V. & Traverso, M., 2019. "Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level," Energy, Elsevier, vol. 176(C), pages 380-391.
  17. Fathi, Soheil & Srinivasan, Ravi & Fenner, Andriel & Fathi, Sahand, 2020. "Machine learning applications in urban building energy performance forecasting: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
  18. Haonan Zhang, 2023. "Leveraging policy instruments and financial incentives to reduce embodied carbon in energy retrofits," Papers 2304.03403, arXiv.org.
  19. Işık, Erdem & Inallı, Mustafa, 2018. "Artificial neural networks and adaptive neuro-fuzzy inference systems approaches to forecast the meteorological data for HVAC: The case of cities for Turkey," Energy, Elsevier, vol. 154(C), pages 7-16.
  20. Piselli, Cristina & Pisello, Anna Laura, 2019. "Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance," Energy, Elsevier, vol. 176(C), pages 667-681.
  21. Cai, Wei & Wen, Xiaodong & Li, Chaoen & Shao, Jingjing & Xu, Jianguo, 2023. "Predicting the energy consumption in buildings using the optimized support vector regression model," Energy, Elsevier, vol. 273(C).
  22. Sean Hay Kim & Jungmin Nam, 2020. "Can Both the Economic Value and Energy Performance of Small- and Mid-Sized Buildings Be Satisfied? Development of a Design Expert System in the Context of Korea," Sustainability, MDPI, vol. 12(12), pages 1-29, June.
  23. Arturas Kaklauskas & Gintautas Dzemyda & Laura Tupenaite & Ihar Voitau & Olga Kurasova & Jurga Naimaviciene & Yauheni Rassokha & Loreta Kanapeckiene, 2018. "Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment," Energies, MDPI, vol. 11(8), pages 1-20, August.
  24. Francesco Calise & Mário Costa & Qiuwang Wang & Xiliang Zhang & Neven Duić, 2018. "Recent Advances in the Analysis of Sustainable Energy Systems," Energies, MDPI, vol. 11(10), pages 1-30, September.
  25. Wang, Guimei & Moayedi, Hossein & Thi, Quynh T. & Mirzaei, Mojtaba, 2024. "Evaluation of heating load energy performance in residential buildings through five nature-inspired optimization algorithms," Energy, Elsevier, vol. 302(C).
  26. Hamidreza Seraj & Ali Bahadori-Jahromi & Shiva Amirkhani, 2024. "Developing a Data-Driven AI Model to Enhance Energy Efficiency in UK Residential Buildings," Sustainability, MDPI, vol. 16(8), pages 1-16, April.
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