Intelligent System for Assessing the Quality of Ore

This paper proposes an integrated approach to the selection of technological solutions for ore preparation, allowing for a combination of intellectual and quantitative methods to justify decisions concerning the management of mining and mineral processing. This intelligent system includes a database for the creation of optimal decisions, models based on neural networks and classical mathematical methods, technical means, technological operations, and organizational techniques that allow for ore quality management measures. A new approach to the classification of fragments of ore fractions is proposed, based on a neural network that has the functionality of finding mineral grains of ore in an image with a subsequent assessment of the degree of its disclosure, making it possible to increase the efficiency of image recognition of ore sections by at least 5% relative to the analytical method of ore analysis.