Comparison between deep learning and fully connected neural network in performance prediction of power cycles: Taking supercritical CO2 Brayton cycle as an example

Chenghao Diao, Tianye Liu, Zhen Yang, Yuanyuan Duan. Comparison between deep learning and fully connected neural network in performance prediction of power cycles: Taking supercritical CO2 Brayton cycle as an example. Int. J. Intell. Syst., 36(12):7682-7708, 2021. [doi]

@article{DiaoLYD21,
  title = {Comparison between deep learning and fully connected neural network in performance prediction of power cycles: Taking supercritical CO2 Brayton cycle as an example},
  author = {Chenghao Diao and Tianye Liu and Zhen Yang and Yuanyuan Duan},
  year = {2021},
  doi = {10.1002/int.22603},
  url = {https://doi.org/10.1002/int.22603},
  researchr = {https://researchr.org/publication/DiaoLYD21},
  cites = {0},
  citedby = {0},
  journal = {Int. J. Intell. Syst.},
  volume = {36},
  number = {12},
  pages = {7682-7708},
}