Abstract
Many mineral predictive models created based on multicriteria decision making (MCDM) methods use only one conceptually-based MCDM technique for data integration and synthesis of the mineral-related predictors. It is noteworthy that relying on just one mode of the conceptually-based data integration technique is often insufficient, as it fails to address the problems the other mode (in terms of either determining the weights of the predictors or by ranking and prioritising the predictors) deals with before the predictors are synthesised. Herein, a hybrid conceptually-based data integration approach comprising the best-worst method (BWM) and the Technique for Order of Preference by Similarity (TOPSIS) methods have been adopted in mapping viable regions of gold mineralisation occurrences over the Abansuoso Area of Ghana's Ashanti Region. The combined use of these two conceptually-based data integration approaches is rare in the literature, particularly in Ghana and West Africa. Based on the aforementioned approach, weights of nine predictors which were sourced from geological and geophysical datasets comprising magnetics and radiometrics were estimated using the BWM approach to determine their comparative importance towards the gold prospect of the study area. Afterwards, the TOPSIS approach was applied to prioritise and rank the various alternatives that makeup the predictors identified for this study. Subsequently, a predictive model that defines the spatial distribution of the mineral prospects of the study area was developed and was referred to as BWM-TOPSIS based mineral potential map (MPM). The BWM-TOPSIS-based MPM was further classified to characterise zones of low, moderate and high mineral potential, with their resulting areal extents being respectively 237.13 km(2), 225.66 km(2) and 127.45 km(2). An evaluation of the MPM developed based on the BWM-TOPSIS technique was conducted by implementing the prediction-area (P-A) plot. Outputs from the P-A plot indicate that 30 % of the study area has high prospect with 70 % of the existing gold locations observed within it. Additionally, the receiver operating characteristics (ROC) curve was used to evaluate the effectiveness of the MPM developed. The MPM generated based on the BWM-TOPSIS approach yielded an AUC score of 0.81; this AUC score indicates that the performance of the predictive model developed is very good.