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Predicting minerals potential helps miners in making wise decisions. In this paper, we present a computerized prototype system called GoldXplorer that enables to predict the existence and distribution of gold (aurum (Au)) at a given location with its geological and geographical factors. With its two intelligent engines based on back-propagation neural network and self-organizing map techniques, GoldXplorer...
Accuracy assessment for map comparison is commonly found in urban planning research, especially for detecting error in remotely sensed imagery data. It is to compare two sources of spatial information. In analyzing such information quantitatively, the two datasets are summarized in a confusion matrix, which is represented in a form of percentage of predicted value against its actual data (ground truth)...
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