Evaluation of Artificial Neural Network-Based Temperature Control for Optimum Operation of Building Envelopes
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- Kalogirou, Soteris A. & Bojic, Milorad, 2000. "Artificial neural networks for the prediction of the energy consumption of a passive solar building," Energy, Elsevier, vol. 25(5), pages 479-491.
- Jin Woo Moon & Kyung-Il Chin & Sooyoung Kim, 2013. "Optimum Application of Thermal Factors to Artificial Neural Network Models for Improvement of Control Performance in Double Skin-Enveloped Buildings," Energies, MDPI, vol. 6(8), pages 1-23, August.
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- Edorta Carrascal-Lekunberri & Izaskun Garrido & Bram Van der Heijde & Aitor J. Garrido & José María Sala & Lieve Helsen, 2017. "Energy Conservation in an Office Building Using an Enhanced Blind System Control," Energies, MDPI, vol. 10(2), pages 1-23, February.
- Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Chatzis, Georgios V. & Biskas, Pandelis N. & Keranidis, Stratos D., 2021. "Minimization of natural gas consumption of domestic boilers with convolutional, long-short term memory neural networks and genetic algorithm," Applied Energy, Elsevier, vol. 299(C).
- Savadkoohi, Marjan & Macarulla, Marcel & Casals, Miquel, 2023. "Facilitating the implementation of neural network-based predictive control to optimize building heating operation," Energy, Elsevier, vol. 263(PB).
- López-Pérez, Luis Adrián & Flores-Prieto, José Jassón, 2023. "Adaptive thermal comfort approach to save energy in tropical climate educational building by artificial intelligence," Energy, Elsevier, vol. 263(PA).
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Keywords
temperature controls; thermal environment; artificial neural network (ANN); predictive and adaptive control; building envelope; energy efficiency;All these keywords.
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