Criteria for the Spatial Distribution of Polymetallic Ore Objects as a Basis for Creating a Predictive Search Model Using a Neural Network Approach

Abstract—This work is aimed at identifying and substantiating criteria that indirectly or actually control ore objects in order to create a predictive neural network model of the metallogenic potential of southeastern Transbaikalia. For this purpose, geological, geophysical and cartographic materials are collected and processed, including the results of the analysis of remote sensing data. Statistical analysis of the array of collected data has made it possible to establish a list of the minimum necessary information to identify criteria for the localization of polymetallic ore objects within the territory of southeastern Transbaikalia. As a result, thematic schemes have been prepared reflecting the relationship between the distribution of known polymetallic mineralization zones and the identified geological and spatial features. A correlation analysis is carried out between all the criteria in order to assess the suitability of using the selected features as input data for a future neural network model.