TY - GEN
T1 - Study on rock bolt support of roadway of coal mine using neural network
AU - Han, Feng Shan
AU - Wu, Xin Li
PY - 2014
Y1 - 2014
N2 - The artificial neural network has been widely used in various field of science and engineering. The artificial neural network has marvelous ability to gain knowledge. In this paper, according to principle of artificial neural network, Model of artificial neural network of rock bolt support of roadway of coal mine has been constructed, Learning system of BP artificial neural network has been trained, it is shown by engineering application that artificial neural network can handle imperfect or incomplete data and it can capture nonlinear and complex relationships among variables of a system. the artificial neural network is emerging as a powerful tool for modeling with the complex system. Method and parameters of rock bolt support of roadway of coal mine can be predicated accurately using artificial neural network, that is of significance and valuable to those subjects of investigation and design of mining engineering.
AB - The artificial neural network has been widely used in various field of science and engineering. The artificial neural network has marvelous ability to gain knowledge. In this paper, according to principle of artificial neural network, Model of artificial neural network of rock bolt support of roadway of coal mine has been constructed, Learning system of BP artificial neural network has been trained, it is shown by engineering application that artificial neural network can handle imperfect or incomplete data and it can capture nonlinear and complex relationships among variables of a system. the artificial neural network is emerging as a powerful tool for modeling with the complex system. Method and parameters of rock bolt support of roadway of coal mine can be predicated accurately using artificial neural network, that is of significance and valuable to those subjects of investigation and design of mining engineering.
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UR - http://www.scopus.com/inward/citedby.url?scp=84887541981&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMM.448-453.3799
DO - 10.4028/www.scientific.net/AMM.448-453.3799
M3 - Conference contribution
AN - SCOPUS:84887541981
SN - 9783037859124
T3 - Applied Mechanics and Materials
SP - 3799
EP - 3802
BT - Renewable Energy and Environmental Technology
T2 - 2013 International Conference on Renewable Energy and Environmental Technology, REET 2013
Y2 - 21 September 2013 through 22 September 2013
ER -