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Projection of early warning identification of hazardous sources of gas explosion accidents in coal mines based on NTM deep learning network

Wenzhe Lai

Wenzhe Lai

Business Administration, Liaoning Technical UniversityHuludao, China
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Lai, Wenzhe
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Liangshan Shao

Liangshan Shao

System Engineering Institute, Liaoning Technical UniversityHuludao, China
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Shao, Liangshan
  
Dec 23, 2022
Projection of early warning identification of hazardous sources of gas explosion accidents in coal mines based on NTM deep learning network's Cover Image
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Published Online: Dec 23, 2022
Page range: 407 - 418
Received: Jul 27, 2022
Accepted: Aug 16, 2022
DOI: https://doi.org/10.2478/amns.2021.2.00299
Keywords
© 2023 Wenzhe Lai et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Calculation analysis of NTM deep learning network algorithm under constraints of multiple disaster factors. NTM, neural Turing machine
Calculation analysis of NTM deep learning network algorithm under constraints of multiple disaster factors. NTM, neural Turing machine

Fig. 2

Calculation analysis of NTM deep learning network algorithm under the constraints of multiple disaster factors (the spatio-temporal constraints are not satisfied). NTM, neural Turing machine
Calculation analysis of NTM deep learning network algorithm under the constraints of multiple disaster factors (the spatio-temporal constraints are not satisfied). NTM, neural Turing machine

Fig. 3

Risk factors and their weights of coal mine gas explosion accidents
Risk factors and their weights of coal mine gas explosion accidents
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Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
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