Pawalai Kraipeerapun

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Quantification of uncertainty in mineral prospectivity prediction is an important process to support decision making in mineral exploration. Degree of uncertainly can identify level of quality in the prediction. This paper proposes an approach to predict degrees of favourability for gold deposits together with quantification of uncertainty in the(More)
This paper presents an approach to the problem of binary classification using ensemble neural networks based on interval neutrosophic sets and bagging technique. Each component in the ensemble consists of a pair of neural networks trained to predict the degree of truth and false membership values. Uncertainties in the prediction are also estimated and(More)