Predicting blast-induced ground vibration using various types of neural networks

Soil Dynamics and Earthquake Engineering

Volumn 30, Issue 11, 2010, Pages 1233-1236

  Monjezi, M ^a   Ahmadi, M ^b   Sheikhan, M ^b   Bahrami, A ^a   Salimi, A R ^b  

^a TARBIAT MODARES UNIVERSITY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

BLASTING OPERATIONS; CIVIL ENGINEERING PROJECTS; COEFFICIENT OF CORRELATION; EFFECTIVE PARAMETERS; GENERAL REGRESSION NEURAL NETWORK; GROUND VIBRATION; MINING OPERATIONS; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; RADIAL BASIS FUNCTION NEURAL NETWORKS; ROOT MEAN SQUARE ERRORS;

CIVIL ENGINEERING; COPPER MINES; FORECASTING; MINING; RADIAL BASIS FUNCTION NETWORKS; SENSITIVITY ANALYSIS; VIBRATION ANALYSIS; WIRELESS SENSOR NETWORKS;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BLASTING; GROUND MOTION; MINE; MINING; PREDICTION; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; VIBRATION;

IRAN;

EID: 77955509487     PISSN: 02677261     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.soildyn.2010.05.005     Document Type: Article

References (26)

1. Singh T.N., Singh V. An intelligent approach to predict and control ground vibration in mines. Geotech Geol Eng 2005, 23(3):249-262.
2. Konya C.J., Walter E.J. S Rock blasting and overbreak control manual 2006, Federal Highway Administration. 3rd ed.
3. Hagan T.N., Kennedy B.J. A practical approach to the reduction of blasting nuisance from surface operation. Aust Min 1977, 69(11):36-46.
4. Mather W. Factors affecting magnitude and frequency of blast-induced ground and air vibrations. Inst Min Metall Trans 1984, 93:A173-A180.
5. Singh S.R., Lamond R.D. Prediction and measurements of blast vibrations. Int J Min Recl Environ 1993, 7(4):149-154.
6. Blair D.P., Jiang J.J. Surface vibration due to a vertical column of explosive. Int J Rock Mech Min Sci Geomech Abstr 1995, 32:149-154.
7. Pal Roy P. Characteristics of ground vibration and structural response to surface and underground blasting. Geotech Geol Eng 1998, 16:151-166.
8. Blair D.P. Statistical models for ground vibration and airblast. Int J Rock Fragm Blast 1999, 3:335-364.
9. Jimeno C.L., Jimeno E., Carcedo F.J.A. Drilling and blasting of rocks 1995, Balkema, Rotterdam.
10. Lu Y. Underground blast induced ground shock and its modeling using artificial neural network. Comput Geotech 2005, 32:164-178.
11. Kalogirou S. Applications of artificial neural networks for energy systems. Appl Energy 2000, 67(2):17-35.
12. Simpson P.K. Artificial neural system: foundation, paradigms, applications and implementations 1990, Pergamon Press, New York.
13. Lippmann R.P. Speech recognition by machines and humans. J. Speech Commun 1997, 22:1-15.
14. Tomam A.W., Goran T. Prediction of subsidence due to underground mining by artifi{ligature}cial neural networks. J Comput Geosci 2003, 29:627-637.
15. Stegemann J.A., Buenfeld N.R. Prediction of unconfined compressive strength of cement paste with pure metal compound additions. J Cem Concr Res 2002, 32:903-913.
16. Hornik K. Multilayer feedforward networks are universal approximators. J Neural Networks 1989, 2:359-366.
17. Funahashi K. On the approximate realization of continuous mappings by neural networks. J Neural Networks 1989, 2(3):183-192.
18. SchÄolkopf B., Smola A. Learning with kernels 2002, MIT Press, Cambridge, MA.
19. Specht D.F. A general regression neural network. J Neural Networks 1991, 2(6):568-576.
20. Roush W.B., Cravener T.L. Artificial neural network prediction of amino acid levels in feed ingredients. J Poult Sci 1997, 76(5):721-727.
21. Ward Systems Group NeuroShell 2 user's manual 1993, Ward Systems Group, Inc., Frederick, MD.
22. Yong-Hun J., Chung-In L. Influence of geological conditions on the powder factor for tunnel blasting. Int J Rock Mech Min Sci 2004, 41:533-538.
23. Khandelwal M., Singh T.N. Prediction of blast induced ground vibrations and frequency in opencast mine-a neural network approach. J Sound Vibr 2006, 289:711-725.
24. Monjezi M., Dehghani H. Evaluation of effect of blasting pattern parameters on backbreak using neural networks. Int J Rock Mech Min Sci 2008, 45:1446-1453.
25. Monjezi M., Bahrami A., Yazdian A., Sayadi A.R. Prediction and controlling of flyrock in blasting operation using artificial neural network. Arabian J Geosci 2009, 10.1007/s12517-009-0091-8.
26. Monjezi M., Bahrami A., Yazdian A. Simultaneous prediction of fragmentation and flyrock in blasting operation using artificial neural networks. Int J Rock Mech Min Sci 2009, 47:476-480.