Overview of computational intelligence for building energy system design
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DOI: 10.1016/j.rser.2019.03.018
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Cited by:
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- 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).
- Dongsu Kim & Jongman Lee & Sunglok Do & Pedro J. Mago & Kwang Ho Lee & Heejin Cho, 2022. "Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends," Energies, MDPI, vol. 15(19), pages 1-30, October.
- Li, Haoran & Zhang, Chenghui & Sun, Bo, 2022. "Deep integration planning of sustainable energies in district energy system and distributed energy station," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
- Qiang, Guofeng & Tang, Shu & Hao, Jianli & Di Sarno, Luigi & Wu, Guangdong & Ren, Shaoxing, 2023. "Building automation systems for energy and comfort management in green buildings: A critical review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
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Keywords
Building energy system; HVAC system design; Optimization; Computational intelligence (CI);All these keywords.
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