Study on rock bolt support of roadway of coal mine using neural network

Feng Shan Han, Xin Li Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationRenewable Energy and Environmental Technology
Pages3799-3802
Number of pages4
DOIs
StatePublished - Jan 1 2014
Event2013 International Conference on Renewable Energy and Environmental Technology, REET 2013 - Jilin, China
Duration: Sep 21 2013Sep 22 2013

Publication series

NameApplied Mechanics and Materials
Volume448-453
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other2013 International Conference on Renewable Energy and Environmental Technology, REET 2013
CountryChina
CityJilin
Period9/21/139/22/13

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Han, F. S., & Wu, X. L. (2014). Study on rock bolt support of roadway of coal mine using neural network. In Renewable Energy and Environmental Technology (pp. 3799-3802). (Applied Mechanics and Materials; Vol. 448-453). https://doi.org/10.4028/www.scientific.net/AMM.448-453.3799