Data-driven predictive control for smart HVAC system in IoT-integrated buildings with time-series forecasting and reinforcement learning
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DOI: 10.1016/j.apenergy.2023.120936
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- Nik, Vahid M. & Hosseini, Mohammad, 2023. "CIRLEM: a synergic integration of Collective Intelligence and Reinforcement learning in Energy Management for enhanced climate resilience and lightweight computation," Applied Energy, Elsevier, vol. 350(C).
- Rosa Francesca De Masi & Nicoletta Del Regno & Antonio Gigante & Silvia Ruggiero & Alessandro Russo & Francesco Tariello & Giuseppe Peter Vanoli, 2023. "The Importance of Investing in the Energy Refurbishment of Hospitals: Results of a Case Study in a Mediterranean Climate," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
- Troy Malatesta & Qilin Li & Jessica K. Breadsell & Christine Eon, 2023. "Distinguishing Household Groupings within a Precinct Based on Energy Usage Patterns Using Machine Learning Analysis," Energies, MDPI, vol. 16(10), pages 1-25, May.
- Sheng Hu & Gongjin Yuan & Kaifeng Hu & Cong Liu & Minghu Wu, 2023. "Non-Intrusive Load Identification Method Based on KPCA-IGWO-RF," Energies, MDPI, vol. 16(12), pages 1-14, June.
- Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Reviewing and Integrating AEC Practices into Industry 6.0: Strategies for Smart and Sustainable Future-Built Environments," Sustainability, MDPI, vol. 15(18), pages 1-27, September.
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Keywords
Smart Facilities Management; Reinforcement Learning; Data-driven Control; Building Automation; Recursive Prediction; Time-Series Forecasting;All these keywords.
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