DocumentCode :
3189776
Title :
Artificial Neural Network´s Application in Intelligent Displacement Back Analysis of Deep Mine Roadway Surrounding Rock
Author :
Chen Haiming ; Wang Renhe
Author_Institution :
Sch. of Civil Eng. & Archit., Anhui Univ. of Sci. & Technol., Huainan, China
Volume :
1
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
808
Lastpage :
811
Abstract :
The parameters of deep mine roadway surrounding rock are very important to the design, construction and stability analysis of the mine roadways. Now there are some shortcomings in the methods to obtain them. It is believed that displacement back analysis method can solve the problems, but there are some defects in it. Aiming at these problems, the paper builds a network of intelligent displacement back analysis of deep mine roadway surrounding rock which is based on MATLAB NN toolbox. Numerical method and orthogonal design method are used to construct the learning samples, to ensure that the samples are in accord with the practical situation and have uniform dispersivity and symmetrical comparability. At last, an example is introduced to show IDBADMRSR´s application. The results show that the method has high computation precision, above 90%, and has overcome some flaws of traditional displacement back analysis methods. The method is feasible and recommendable.
Keywords :
civil engineering computing; design engineering; learning (artificial intelligence); mining industry; neural nets; roads; MATLAB NN toolbox; artificial neural network; deep mine roadway; intelligent displacement back analysis; numerical method; orthogonal design method; stability analysis; Artificial intelligence; Artificial neural networks; Civil engineering; Computer networks; Design automation; Design methodology; Intelligent networks; Neural networks; Optimization methods; Stability analysis; artificial neural network; deep mine roadway; displacement back analysis; orthogonal design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.807
Filename :
5522582
Link To Document :
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