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Auezov University highlighted the role of artificial intelligence in modernizing geological exploration
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Auezov SKU hosted the international scientific conference “Integral Operators in Functional Spaces and Harmonic Analysis”.
During the event, N. M. Temirbekov – Vice President of the National Academy of Engineering of the Republic of Kazakhstan for Artificial Intelligence and Digital Development, Doctor of Physical and Mathematical Sciences; and Professor at Al-Farabi Kazakh National University, presented a report “Machine Learning Methods for Geological Data Processing and Forecasting Ore-Prospective Areas”.
The speaker emphasised the importance of digitising the geological sector, systematising subsurface data and integrating artificial intelligence technologies into geological exploration.
Within the framework of the BR27100483 scientific and technical program, new approaches were presented for identifying ore-prospective areas using artificial intelligence and Earth remote sensing technologies, based on a comprehensive analysis of geological, geophysical, geochemical and satellite data.
The research identified prospective sites of lithium mineralisation in the Kalba-Narym metallogenic zone in East Kazakhstan, demonstrating the high reliability of the developed models.
The scientific results presented at the conference showed that artificial intelligence offers significant potential for modernising geological exploration, enhancing the efficiency of mineral discovery and providing a scientific basis for evaluating Kazakhstan's mineral resource potential.
During the event, N. M. Temirbekov – Vice President of the National Academy of Engineering of the Republic of Kazakhstan for Artificial Intelligence and Digital Development, Doctor of Physical and Mathematical Sciences; and Professor at Al-Farabi Kazakh National University, presented a report “Machine Learning Methods for Geological Data Processing and Forecasting Ore-Prospective Areas”.
The speaker emphasised the importance of digitising the geological sector, systematising subsurface data and integrating artificial intelligence technologies into geological exploration.
Within the framework of the BR27100483 scientific and technical program, new approaches were presented for identifying ore-prospective areas using artificial intelligence and Earth remote sensing technologies, based on a comprehensive analysis of geological, geophysical, geochemical and satellite data.
The research identified prospective sites of lithium mineralisation in the Kalba-Narym metallogenic zone in East Kazakhstan, demonstrating the high reliability of the developed models.
The scientific results presented at the conference showed that artificial intelligence offers significant potential for modernising geological exploration, enhancing the efficiency of mineral discovery and providing a scientific basis for evaluating Kazakhstan's mineral resource potential.
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