Open Access
Issue
E3S Web Conf.
Volume 356, 2022
The 16th ROOMVENT Conference (ROOMVENT 2022)
Article Number 02027
Number of page(s) 5
Section Underground Environment and Specialized Application
DOI https://doi.org/10.1051/e3sconf/202235602027
Published online 31 August 2022
  1. Qiang Chen. Heat transfer and energy saving potential prediction of the tunnel. Xi,an Univ. of Arch. & Tech, 2015. [Google Scholar]
  2. Margaux Peltier, Alessandro F. Rotta Loria, Loïc Lepage, Etienne Garin, Lyesse Laloui, Numerical investigation of the convection heat transfer driven by airflows in underground tunnels, Applied Thermal Engineering, Volume 159, 2019, 113844 [Google Scholar]
  3. Zou B, Zhou J, Xue S, Di HW, Xu W, Jiang K, Lu T, Hu K, Xu C. Study on the effect of ventilation and heat exchange in underground traffic caverns of Yixing pumped storage power station Hydropower Energy Science, 2017, 35(12):104-107 [Google Scholar]
  4. Angui Li, Changqing Yang, Tong Ren, Modeling and parametric studies for convective heat transfer in large, long and rough circular cross-sectional underground tunnels, Energy and Buildings, Volume 127, 2016, Pages 259-267. [Google Scholar]
  5. Shu M.J., Liu Shunbo, Li Hui. Numerical simulation of wet air condensation in deep buried air ducts. Building Energy Efficiency, 2015(2):9-12. [Google Scholar]
  6. Johnstone, C. Sulungu, E.D. Application of neural network in prediction of temperature: a review. Neural Comput & Applic 33, 11487–11498 (2021) [CrossRef] [Google Scholar]
  7. Bo Xu, Han-Cheng Dan, Liang Li. Temperature prediction model of asphalt pavement in cold regions based on an improved BP neural network. Applied Thermal Engineering, Volume 120, 2017, Pages 568-580 [CrossRef] [Google Scholar]
  8. Chen M. MATLAB neural network principles and examples in a nutshell. Beijing: Tsinghua University Press, 2013: 166-17 [Google Scholar]
  9. Weipeng Cao, Xizhao Wang, Zhong Ming, Jinzhu Gao. A review on neural networks with random weights. Neurocomputing, Volume 275, 2018, Pages 278-287 [CrossRef] [Google Scholar]
  10. Guo Dan. Analysis on the Heat Transfer between Air and Underground Tunnel. Building Energy & Environment, 2012(05):52+85-87 [Google Scholar]
  11. Chen Qiang. Prediction of heat transfer effect and energy saving potential of tunnel air. Xi’an University of Architecture and Technology, 2015 [Google Scholar]

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