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Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method

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Cited by:

  1. Wangqi Xiong & Jiandong Wang, 2020. "Minimizing Power Consumption of an Experimental HVAC System Based on Parallel Grid Searching," Energies, MDPI, vol. 13(8), pages 1-18, April.
  2. Bustamante, Waldo & Uribe, Daniel & Vera, Sergio & Molina, Germán, 2017. "An integrated thermal and lighting simulation tool to support the design process of complex fenestration systems for office buildings," Applied Energy, Elsevier, vol. 198(C), pages 36-48.
  3. Qin, Haosen & Yu, Zhen & Li, Tailu & Liu, Xueliang & Li, Li, 2023. "Energy-efficient heating control for nearly zero energy residential buildings with deep reinforcement learning," Energy, Elsevier, vol. 264(C).
  4. Alibabaei, Nima & Fung, Alan S. & Raahemifar, Kaamran & Moghimi, Arash, 2017. "Effects of intelligent strategy planning models on residential HVAC system energy demand and cost during the heating and cooling seasons," Applied Energy, Elsevier, vol. 185(P1), pages 29-43.
  5. Abhinandana Boodi & Karim Beddiar & Malek Benamour & Yassine Amirat & Mohamed Benbouzid, 2018. "Intelligent Systems for Building Energy and Occupant Comfort Optimization: A State of the Art Review and Recommendations," Energies, MDPI, vol. 11(10), pages 1-26, September.
  6. Perera, A.T.D. & Wickramasinghe, P.U. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "Machine learning methods to assist energy system optimization," Applied Energy, Elsevier, vol. 243(C), pages 191-205.
  7. Nishant Raj Kapoor & Ashok Kumar & Tabish Alam & Anuj Kumar & Kishor S. Kulkarni & Paolo Blecich, 2021. "A Review on Indoor Environment Quality of Indian School Classrooms," Sustainability, MDPI, vol. 13(21), pages 1-43, October.
  8. Wang, Zeyu & Liu, Jian & Zhang, Yuanxin & Yuan, Hongping & Zhang, Ruixue & Srinivasan, Ravi S., 2021. "Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  9. Yang, Shiyu & Wan, Man Pun & Chen, Wanyu & Ng, Bing Feng & Dubey, Swapnil, 2020. "Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization," Applied Energy, Elsevier, vol. 271(C).
  10. Weixiang Zhang & Jieli Sui, 2025. "HypE-GA based study on optimal design of standard floor facade windowing of high-rise office buildings facing energy saving in heating, cooling and lighting," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-20, February.
  11. Iivo Metsä-Eerola & Jukka Pulkkinen & Olli Niemitalo & Olli Koskela, 2022. "On Hourly Forecasting Heating Energy Consumption of HVAC with Recurrent Neural Networks," Energies, MDPI, vol. 15(14), pages 1-20, July.
  12. Cui, Can & Zhang, Xin & Cai, Wenjian, 2020. "An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model," Applied Energy, Elsevier, vol. 264(C).
  13. Jazizadeh, Farrokh & Jung, Wooyoung, 2018. "Personalized thermal comfort inference using RGB video images for distributed HVAC control," Applied Energy, Elsevier, vol. 220(C), pages 829-841.
  14. Jing, Gang & Cai, Wenjian & Zhang, Xin & Cui, Can & Liu, Hongwu & Wang, Cheng, 2020. "An energy-saving control strategy for multi-zone demand controlled ventilation system with data-driven model and air balancing control," Energy, Elsevier, vol. 199(C).
  15. Salata, Ferdinando & Golasi, Iacopo & di Salvatore, Maicol & de Lieto Vollaro, Andrea, 2016. "Energy and reliability optimization of a system that combines daylighting and artificial sources. A case study carried out in academic buildings," Applied Energy, Elsevier, vol. 169(C), pages 250-266.
  16. Lei, Yunkai & Hou, Kai & Wang, Yue & Jia, Hongjie & Zhang, Pei & Mu, Yunfei & Jin, Xiaolong & Sui, Bingyan, 2018. "A new reliability assessment approach for integrated energy systems: Using hierarchical decoupling optimization framework and impact-increment based state enumeration method," Applied Energy, Elsevier, vol. 210(C), pages 1237-1250.
  17. Antonio Del Corte-Valiente & José Luis Castillo-Sequera & Ana Castillo-Martinez & José Manuel Gómez-Pulido & Jose-Maria Gutierrez-Martinez, 2017. "An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems," Energies, MDPI, vol. 10(2), pages 1-18, February.
  18. Hou, D. & Evins, R., 2024. "A protocol for developing and evaluating neural network-based surrogate models and its application to building energy prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
  19. Orosz, Matthew & Altes-Buch, Queralt & Mueller, Amy & Lemort, Vincent, 2018. "Experimental validation of an electrical and thermal energy demand model for rapid assessment of rural health centers in sub-Saharan Africa," Applied Energy, Elsevier, vol. 218(C), pages 382-390.
  20. Krese, Gorazd & Lampret, Žiga & Butala, Vincenc & Prek, Matjaž, 2018. "Determination of a Building's balance point temperature as an energy characteristic," Energy, Elsevier, vol. 165(PB), pages 1034-1049.
  21. Byung-Ki Jeon & Eui-Jong Kim, 2021. "LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
  22. Baloch, Ashfaque Ahmed & Shaikh, Pervez Hameed & Shaikh, Faheemullah & Leghari, Zohaib Hussain & Mirjat, Nayyar Hussain & Uqaili, Muhammad Aslam, 2018. "Simulation tools application for artificial lighting in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3007-3026.
  23. Haosen Qin & Zhen Yu & Tailu Li & Xueliang Liu & Li Li, 2022. "Heating Control Strategy Based on Dynamic Programming for Building Energy Saving and Emission Reduction," IJERPH, MDPI, vol. 19(21), pages 1-27, October.
  24. Chong, Kok-Keong & Onubogu, Nneka Obianuju & Yew, Tiong-Keat & Wong, Chee-Woon & Tan, Woei-Chong, 2017. "Design and construction of active daylighting system using two-stage non-imaging solar concentrator," Applied Energy, Elsevier, vol. 207(C), pages 45-60.
  25. Panagiotis Michailidis & Iakovos Michailidis & Socratis Gkelios & Elias Kosmatopoulos, 2024. "Artificial Neural Network Applications for Energy Management in Buildings: Current Trends and Future Directions," Energies, MDPI, vol. 17(3), pages 1-47, January.
  26. Afroz, Zakia & Shafiullah, GM & Urmee, Tania & Higgins, Gary, 2018. "Modeling techniques used in building HVAC control systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 64-84.
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