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Prediction of blast induced ground vibrations and frequency in opencast mine: A neural network approach

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Title Prediction of blast induced ground vibrations and frequency in opencast mine: A neural network approach
 
Creator KHANDELWAL, M
SINGH, TN
 
Description This paper presents the application of neural network for the prediction of ground vibration and frequency by all possible influencing parameters of rock mass, explosive characteristics and blast design. To investigate the appropriateness of this approach, the predictions by ANN is also compared with conventional statistical relation. Network is trained by 150 dataset with 458 epochs and tested it by 20 dataset. The correlation coefficient determined by ANN is 0.9994 and 0.9868 for peak particle velocity (PPV) and frequency while correlation coefficient by statistical analysis is 0.4971 and 0.0356. (c) 2005
 
Publisher ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
 
Date 2011-07-12T20:31:08Z
2011-12-26T12:47:46Z
2011-12-27T05:39:47Z
2011-07-12T20:31:08Z
2011-12-26T12:47:46Z
2011-12-27T05:39:47Z
2006
 
Type Article
 
Identifier JOURNAL OF SOUND AND VIBRATION, 289(4-5), 711-725
0022-460X
http://dx.doi.org/10.1016/j.jsv.2005.02.044
http://dspace.library.iitb.ac.in/xmlui/handle/10054/3587
http://hdl.handle.net/10054/3587
 
Language en