Application of soft computing in predicting rock fragmentation to reduce environmental blasting side effects

Arabian Journal of Geosciences

Volumn 7, Issue 2, 2014, Pages 505-511

  Monjezi, Masoud ^a   Mohamadi, Hasan Ali ^a   Barati, Bahare ^b   Khandelwal, Manoj ^c  

^a TARBIAT MODARES UNIVERSITY   (Iran)

^b SHAHID BAHONAR UNIVERSITY OF KERMAN   (Iran)

^c MAHARANA PRATAP UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (India)

Author keywords

Artificial neural network; Fragmentation; Sungun copper mine

Indexed keywords

EID: 84895074700     PISSN: 18667511     EISSN: 18667538     Source Type: Journal    
DOI: 10.1007/s12517-012-0770-8     Document Type: Article

References (29)

1. Abbassi A, Bahar L (2005) Application of neural network for the modeling and control of evaporative condenser cooling load. Appl Therm Eng 25: 3176-3186.
2. Alsmadi MKS, Omar KB, Noah SA (2009) Back propagation algorithm: the best algorithm among the multi-layer perceptron algorithm. Int J Comput Sci Netw Secur 9: 378-383.
3. Anderson JA (1995) An introduction to neural networks. MIT, Cambridge, MA, pp 672. ISBN: 10: 0262011441.
4. Chauvin Y, Rumelhart DE (1995) Backpropagation: theory, architectures and applications. Erlbaum, Mahwah, NJ, p 561. ISBN 080581258X.
5. Eberhart RC, Dobbins RW (1990) Neural network PC tools: a practical guide. Academic, San Diego, CA.
6. Gokceoglu C, Zorlu K (2004) A fuzzy model to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock. Eng Appl Artif Intell 17: 61-72.
7. Gorucu FB, Ertekin T, Bromhal, G, Smith D, Sams N, Jikich S (2005) Development of a neuro-simulation tool for coal bed methane recovery and CO2 sequestration. International Coalbed Methane Symposium, Tuscaloosa. AL. Paper 0505.
8. Grima A, Verhoef PNW (1999) Forecasting rock trencher performance using fuzzy logic. Int J Rock Mech Min Sci 36(4): 413-432.
9. Jong YH, Lee CI (2004) Influence of geological conditions on the powder factor for tunnel blasting. Int J Rock Mech Min Sci 41: 533-538.
10. Khandelwal M (2012) Prediction of safe charge to protect surrounding structures using support vector machine. Geotech Geol Eng 30(4): 859-867.
11. Khandelwal M, Kankar PK (2011) Prediction of blast-induced air overpressure using support vector machine. Arab J Geosci 4(3-4): 427-433.
12. Khandelwal M, Singh TN (2009) Prediction of blast-induced ground vibration using artificial neural network. Int J Rock Mech Min Sci 46: 1214-1222.
13. Khandelwal M, Singh TN (2011) Predicting elastic properties of schistose rocks from unconfined strength using intelligent approach. Arab J Geosci 4(3-4): 435-442.
14. Kosko B (1994) Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. New Delhi, Prentice-Hall, pp 12-17.
15. Maerz NH, Franklin JA, Rothenburg L, Coursen DL (1986) Measurement of rock fragmentation by digital photoanalysis. Proceedings, Fifth International Congress International Society of Rock Mechanics. pp. 687-682.
16. Monjezi M, Dehghani H (2008) Evaluation of effect of blasting pattern parameters on back break using neural networks. Int J Rock Mech Min Sci 45: 1446-1453.
17. Monjezi M, Yazdian A, Hesami SM (2006) Use of back propagation neural network to estimate burden in tunnel blasting. J Mines Metals Fuels 54: 424-429.
18. Monjezi M, Hesami SM, Khandelwal M (2011) Superiority of neural networks for pillar stress prediction in bord and pillar method. Arab J Geosci 4(5-6): 845-853.
19. Neaupane KM, Adhikari NR (2006) Prediction of tunneling-induced ground movement with the multi-layer perceptron. Int J Tunnel Undergr Space Technol 21: 151-159.
20. Neaupanea KM, Achet SH (2004) Use of backpropagation neural network for landslide monitoring, a case study in the higher Himalaya. J Eng Geol 74: 213-226.
21. Nie SL, Rustan A, (1987) Technique and procedures in analysing fragmentation after blasting by photographic method. Proceedings, Second International Symposium on Rock Fragmentation by Blasting, Keystone, Colorado, U. S. A. pp. 102-113.
22. Peisheng L, Youhui X, Dunxi Y, Xuexin S (2005) Prediction of grindability with multivariable regression and neural network in Chinese coal. Fuel 84: 2384-2388.
23. Rumelhart D, Hinton G, Williams R (1986) Learning representations by backpropagating error. Nature 323: 533-536.
24. Simpson PK (1990) Artificial neural system: foundation, paradigm, application and implementations. Pergamon, New York.
25. Tampe SS, Kulkarani BD, Deshpande PB (1996) Elements of artificial neural networks with selected applications in chemical engineering, and chemical & biological sciences, simulation & advanced controls. Louisville, KY.
26. Tawadrous AS, Katsabanis PD (2006) Prediction of surface crown pillar stability using artificial neural networks. Int J Num Anal Methods Geomech 31: 917-931.
27. Trippi RR, Turban E (1996) Neural networks in finance and investing-using artificial intelligence to improve real-world performance. McGraw-Hill, New York, Revised ed.
28. Wasserman PD (1989) Neural computing theory and practice. van Nostrand Reinhold, New York.
29. Yang Y, Zhang Q (1997) A hierarchical analysis for rock engineering using artificial neural networks. J Rock Mech Rock Eng 30: 207-222.