Cite
Prediction and evaluation of energy and exergy efficiencies of a nanofluid-based photovoltaic-thermal system with a needle finned serpentine channel using random forest machine learning approach.
MLA
Si, Yuanlei, et al. “Prediction and Evaluation of Energy and Exergy Efficiencies of a Nanofluid-Based Photovoltaic-Thermal System with a Needle Finned Serpentine Channel Using Random Forest Machine Learning Approach.” Engineering Analysis with Boundary Elements, vol. 151, June 2023, pp. 328–43. EBSCOhost, https://doi.org/10.1016/j.enganabound.2023.03.009.
APA
Si, Y., Brumercik, F., Yang, C., Glowacz, A., Ma, Z., Siarry, P., Sulowicz, M., Gupta, M. K., & Li, Z. (2023). Prediction and evaluation of energy and exergy efficiencies of a nanofluid-based photovoltaic-thermal system with a needle finned serpentine channel using random forest machine learning approach. Engineering Analysis with Boundary Elements, 151, 328–343. https://doi.org/10.1016/j.enganabound.2023.03.009
Chicago
Si, Yuanlei, Frantisek Brumercik, Chunsheng Yang, Adam Glowacz, Zhenjun Ma, Patrick Siarry, Maciej Sulowicz, Munish Kumar Gupta, and Zhixiong Li. 2023. “Prediction and Evaluation of Energy and Exergy Efficiencies of a Nanofluid-Based Photovoltaic-Thermal System with a Needle Finned Serpentine Channel Using Random Forest Machine Learning Approach.” Engineering Analysis with Boundary Elements 151 (June): 328–43. doi:10.1016/j.enganabound.2023.03.009.