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Theoretical Basis in Regression Model Based Selection of the Most Cost Effective Parameters of Hard Rock Surface Mining

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dc.creator Massawe, Antipas T. S.
dc.creator Baruti, Karim R.
dc.creator Gongo, Paul S. M.
dc.date 2016-06-30T11:57:09Z
dc.date 2016-06-30T11:57:09Z
dc.date 2011
dc.date.accessioned 2018-03-27T08:32:24Z
dc.date.available 2018-03-27T08:32:24Z
dc.identifier Antipas TS, M., Karim R, B. and Paul SM, G., 2011. Theoretical Basis in Regression Model Based Selection of the Most Cost Effective Parameters of Hard Rock Surface Mining. Engineering, 2011.
dc.identifier http://hdl.handle.net/20.500.11810/2810
dc.identifier 10.4236/eng.2011.32018
dc.identifier.uri http://hdl.handle.net/20.500.11810/2810
dc.description What determines selection of the most cost effective parameters of hard rock surface mining is consideration of all alternative variants of mine design and the conflicting effect of their parameters on cost. Consideration could be realized based on the mathematical model of the cumulative influence of rockmass and mine design variables on the overall cost per ton of the hard rock drilled, blasted, hauled and primary crushed. Available works on the topic mostly dwelt on four processes of hard rock surface mining separately. This paper dwells on the theoretical part of a research proposed to enhance effectiveness in the selection of the parameters of hard rock surface mining design based on the regression model of overall cost per tonne of the rock mined fit on the determinant variations of rockmass and mine design. The regression model could be developed based on the statistical data generated by many of the hard rock surface mines operating in variable conditions of rockmass and mine design worldwide. Also, a regression model based general algorithm has been formulated for the development of software and computer aided selection of the most cost effective parameters of hard rock surface mining.
dc.language en
dc.publisher Scientific Research
dc.subject Parameters of Rockmass
dc.subject Parameters of Mining Design
dc.subject Regression Model
dc.subject Algorithm of Selection
dc.title Theoretical Basis in Regression Model Based Selection of the Most Cost Effective Parameters of Hard Rock Surface Mining
dc.type Journal Article, Peer Reviewed


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