On the Potential of Geospatial Artificial Intelligence - GeoAl in Solving Problems of Development of Metal-Bearing Technogenic Deposits
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Abstract
Solid mineral wastes generated as a result of mining and processing of minerals represent a significant environmental problem of the geosphere. Their accumulations in terms of scale and content are deservedly referred to technogenic deposits, the development of which is of great interest both for modern and upcoming digital-industrial revolution called "Industry-4.0". It is noted that the effectiveness of this activity will depend on the efficiency and adequacy of the assessment of the environmental and economic feasibility of extracting the target components, on the quantitative assessment of the volume of accumulation of the extracted element, the possibility of extending its life cycle, on the expected composition of by-products and their consumer value, on the minimum acceptable level of profitability of the selected development technology, as well as - on the rate of re-accumulation and environmental inertness of the waste generated during recycling. In connection with the above, this study emphasizes the importance and necessity of the application of modern hybrid geospatial artificial intelligence (GeoAI), which includes the synergy of general artificial intelligence (AI) based on adaptive neuro-fuzzy inference system (ANFIS) with geographical information systems (GIS). Consequently, in order to increase the efficiency of GeoAI application and to obtain accurate and effective results in solving the set tasks, it is recommended and justified the expediency of combining the knowledge of neural networks and fuzzy logic with GIS data, where the latter will serve as a source-storage of reference (initial/boundary) data on the current and desired for achieving the set goal changes in the developed technogenic deposits.
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References
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