Applying Neural Network to Predict Roadway Surrounding Rock Displacement: Fid-Bau Portal

Fachinformationsdienst BAUdigital

A platform for research: civil engineering, architecture and urbanism

Applying Neural Network to Predict Roadway Surrounding Rock Displacement

Jun-Yi, TANG / Min, ZHANG / Miao, ZHANG / Wan-Jun, YU / Yu, TIAN

Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.

Access

Check availability in my library

Order at Subito €

Page navigation

Document information

Export, share and cite

Applying Neural Network to Predict Roadway Surrounding Rock Displacement

Jun-Yi, TANG / Min, ZHANG / Miao, ZHANG / Wan-Jun, YU / Yu, TIAN

Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.

Applying Neural Network to Predict Roadway Surrounding Rock Displacement

Jun-Yi, TANG / Min, ZHANG / Miao, ZHANG / Wan-Jun, YU / Yu, TIAN

Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.

Access

Check availability in my library

Order at Subito €

Page navigation

Document information

Export, share and cite

Document information

Title:

Applying Neural Network to Predict Roadway Surrounding Rock Displacement

Contributors:

Jun-Yi, TANG (author) / Min, ZHANG (author) / Miao, ZHANG (author) / Wan-Jun, YU (author) / Yu, TIAN (author)

Published in:

2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) ; 148-151

Publication date:

2020-11-18

Size:

3066192 byte

ISBN:

978-1-7281-8022-9 , 978-1-7281-8021-2

ISSN:

DOI:

https://doi.org/10.1109/ICIIBMS50712.2020.9336394

Type of media:

Conference paper

Type of material:

Electronic Resource

Language:

English

Similar titles

The Roadway Surrounding Rock Delaminating Displacement Monitoring Technology Based on Moiré Technique

Luo, Fang Liang ;An, Li Qian ;Mao, Ling Tao | Trans Tech Publications | 2011

Soft rock roadway surrounding rock stability monitoring device

ZHAO CHUANXIANG / WU DEYI / HUANG YISHOU et al. | European Patent Office | 2024

Free access

Roadway (tunnel) surrounding rock flexible supporting method

WU HAO / WANG WANLU / LI SHUJIAN et al. | European Patent Office | 2024

Free access

Surrounding Rock Classification in Deep Roadway of Coal Mine

Liu, Bin ;Liu, Quan Sheng | Trans Tech Publications | 2011

Quick-setting grouting material for reinforcing surrounding rock of roadway

ZHENG LIANCHENG / YE JIAGEN / HAN WENYU et al. | European Patent Office | 2024

Free access