A LSTM-RNN based intelligent control approach for temperature and humidity environment of urban utility tunnels

Fang-Le Peng, Yong-Kang Qiao, Chao Yang

Open source

DOI
10.1016/j.heliyon.2023.e13182
Published
2023-02
Container
Heliyon
Publisher
Elsevier BV
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.heliyon.2023.e13182,
  title = {A LSTM-RNN based intelligent control approach for temperature and humidity environment of urban utility tunnels},
  author = {Fang-Le Peng and Yong-Kang Qiao and Chao Yang},
  year = {2023},
  journal = {Heliyon},
  doi = {10.1016/j.heliyon.2023.e13182},
  url = {https://doi.org/10.1016/j.heliyon.2023.e13182}
}

RIS

TY  - JOUR
TI  - A LSTM-RNN based intelligent control approach for temperature and humidity environment of urban utility tunnels
AU  - Fang-Le Peng
AU  - Yong-Kang Qiao
AU  - Chao Yang
PY  - 2023
JO  - Heliyon
DO  - 10.1016/j.heliyon.2023.e13182
UR  - https://doi.org/10.1016/j.heliyon.2023.e13182
ER  -

APA

Peng, F., Qiao, Y., & Yang, C. (2023). A LSTM-RNN based intelligent control approach for temperature and humidity environment of urban utility tunnels. Heliyon. https://doi.org/10.1016/j.heliyon.2023.e13182

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