Prediction of Backbreak in the Blasting Operations using Artificial Neural Network (ANN) Model and Statistical Models (Case study: Gol-e-Gohar Iron Ore Mine No. 1)
AbbAS KhAjouEi SirjAni, F. Sereshki, M. Ataei, MohAMMAd AMiri hoSSEini
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期刊介绍：
Archives of Mining Sciences (AMS) is concerned with original research, new developments and case studies in mining sciences and energy, civil engineering and environmental engineering. The journal provides an international forum for the publication of high quality research results in:
mining technologies,
mineral processing,
stability of mine workings,
mining machine science,
ventilation systems,
rock mechanics,
termodynamics,
underground storage of oil and gas,
mining and engineering geology,
geotechnical engineering,
tunnelling,
design and construction of tunnels,
design and construction on mining areas,
mining geodesy,
environmental protection in mining,
revitalisation of postindustrial areas.
Papers are welcomed on all relevant topics and especially on theoretical developments, analytical methods, numerical methods, rock testing, site investigation, and case studies.
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