Application research of DHNN model in prediction of classification of rockburst intensity

Application research of DHNN model in prediction of classification of rockburst intensity

In view of problems of randomness and subjectivity in determining weight of existing rockburst prediction methods，a discrete Hopfield neural network (DHNN) model for prediction of classification of rockburst intensity was proposed。The model selects stress coefficient, rockbrittleness coefficient and...

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Bibliographic Details
Main Authors: XU Jia, CHEN Junzhi, LIU Chenyu, WANG Jiaxin, LONG Gang, LI Chunyi
Format: Article
Language:zho
Published: Editorial Department of Industry and Mine Automation 2018-01-01
Series:Gong-kuang zidonghua
Subjects:
coal mining
deep underground engineering
rockburst intensity
classification prediction
elastic energy
rock brittleness coefficient
discrete hopfield neural network
Online Access:http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2017050027

Internet

http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671-251x.2017050027

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