Research on Prediction of Rating of Rockburst Based on BP Neural Network
With the development of economic construction, underground space development continues to move towards the deep. "More, long, big, deep," will be the general trend of the development of underground engineering in the 21st century. Rock burst is a kind of sudden geological disasters with a...
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Published in | The open civil engineering journal Vol. 8; no. 1; pp. 463 - 469 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
31.12.2014
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Online Access | Get full text |
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Summary: | With the development of economic construction, underground space development continues to move towards
the deep. "More, long, big, deep," will be the general trend of the development of underground engineering in the 21st
century. Rock burst is a kind of sudden geological disasters with a higher frequency in deep tunnel construction. Rock
burst prediction has very important significance for the construction of underground engineering in highland stress area.
This paper described the mechanism of rockburst. The researchers systematically analyzed relevant factors of rockburst.
In this paper, the principle and application of Back-Propagation (BP) neural network were introduced, and to improve the
algorithm of neural network, the NNT prediction model was set up. The author have taken the seven parameters including
(as input values): Index of brittleness, Ratio of Strength stress, Ratio of maximum stress to minimum stress, Depth of engineering,
Completeness of rockmass, Structural strength, Depth of pit for rock burst. The results of rockburst also proved
the prediction model has high accuracy and stability, indicating that the model has a good prospect in the rock burst forecasting. |
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ISSN: | 1874-1495 1874-1495 |
DOI: | 10.2174/1874149501408010463 |