Uncertainty in mineral prospectivity prediction
This paper presents an approach to the prediction of mineral prospectivity that provides an assessment of uncertainty. Two feedforward backpropagation neural networks are used for the prediction. One network is used to predict degrees of favourability for deposit and another one is used to predict degrees of likelihood for barren, which is opposite to deposit. These two types of values are represented in the form of truth-membership and false-membership, respectively. Uncertainties of type...[Show more]
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