Using Run-of-mine Tonnage and Grade to Predict Cost and Categorize Gold Mines: Analysing the Application of Logistic Regression Analysis and ANN - Baruti, Karim Rajabu (Current Approaches in Engineering Research and Technology Vol. 5, 2024)
The increase in demand for gold in the world over the past three decades has witnessed an increase in the gold price to accommodate more efforts of mining and exploration in the gold mining industry. Categorization of gold mines based on rom-tonnage and grade would be more useful if it can statistically be used to predict the cost of gold mining. This paper focuses on establishing logistic and ANN models of the cost effect of run-of-mine tonnage and grade in the justification of the categorization of gold mines. Gold mines could be categorized based on the abilities of rom-grade and rom-tonnage to predict cost. The data used in the generation of the logistic and ANN models were cash-cost as the dependent variable vs. rom-grade, and rom-tonnage as independent variables together with the type of mine. The data were obtained from 160 gold mines selected from the top 20 gold-rich countries in the period of 7 years from 2002 to 2008. The first analysis was the Logistic Regression Analysis which was carried out in the SPSS software to determine the probability of occurrence of low cost given rom-grade and rom-tonnage for either an open pit, underground, or both mines together. The second analysis was based on ANN which was carried out to develop the ANN model. Using a Multilayer perceptron neural network and backpropagation, the ANN Model was trained to predict the cost. The main results for both logistic and ANN Models indicated that only rom-grade with a cut-off value of 5.385 g/t can be used to categorize gold mines as low and high grade while there was not enough evidence to categorize gold mines based on their rom-tonnage. The only evidence provided by ANN indicated that the normalized importance of rom-grade was 100% while for rom tonnage was 48.65. The full models established in this study have a percentage correct of 62.9 for logistic and 64 for ANN compared to 57.9 by guess. The relationship between cost vs. rom-grade and rom-tonnage indicated that only 6.9 percent of the cost is accounted for by rom-grade and rom-tonnage. This is a weak relation indicating that rom-grade and rom-tonnage are not the only determinants and therefore on their own must be used with precaution. Validation of the model agrees well with the actual results. Future research should focus on the other determinants which account for the remaining unaccounted 37.6%.