Neural-Fuzzy Model for Gold Minerals Detection
A.V. Kamenev, Ф.Ф. Пащенко, Alexander F. Pashchenko · 2017
A neural-fuzzy network model is proposed for detection of gold minerals. Fuzzy logic allows us to model systems without requiring a precise mathematical model. It helps to apply hybrid algorithm for creating model of systems with high uncertainties. Described intelligent algorithm uses geological data for minerals localization. We apply it to real data - “Taldan region” and get accepted results based only on geological fractures as input for neural-fuzzy network. All achieved results give possibility to scale our model to process all set of geological data and help geologists to find new minerals.