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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Assessment of Uncertainty in Mineral Prospectivity Prediction Using Interval Neutrosophic Set
verfasst von : Pawalai Kraipeerapun, Chun Che Fung, Warick Brown
Erschienen in: Computational Intelligence and Security
Verlag: Springer Berlin Heidelberg
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Accurate spatial prediction of mineral deposit locations is essential for the mining industry. The integration of Geographic Information System (GIS) data with soft computing techniques can improve the accuracy of the prediction of mineral prospectivity. But uncertainty still exists. Uncertainties always exist in GIS data and in the processing required to make predictions. Quantification of uncertainty in mineral prospectivity prediction can support decision making in regional-scale mineral exploration. This research deals with these uncertainties. In this study, interval neutrosophic sets are combined with existing soft computing techniques to express uncertainty in the prediction of mineral deposit locations.